├── data
    ├── MCTest
    │   ├── LICENSE.pdf
    │   ├── mc160.dev.ans
    │   ├── mc500.dev.ans
    │   ├── mc160.train.ans
    │   ├── mc500.train.ans
    │   ├── README.txt
    │   ├── mc160.dev.tsv
    │   └── mc160.dev.txt
    ├── MCTestAnswers
    │   ├── LICENSE.pdf
    │   ├── mc160.test.ans
    │   ├── mc500.test.ans
    │   └── README.txt
    └── stopwords.txt
├── .gitignore
├── mctest.proto
├── README.md
├── baseline-embed.py
├── baseline.py
└── parse.py


/data/MCTest/LICENSE.pdf:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/mcobzarenco/mctest/HEAD/data/MCTest/LICENSE.pdf


--------------------------------------------------------------------------------
/data/MCTestAnswers/LICENSE.pdf:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/mcobzarenco/mctest/HEAD/data/MCTestAnswers/LICENSE.pdf


--------------------------------------------------------------------------------
/data/MCTest/mc160.dev.ans:
--------------------------------------------------------------------------------
 1 | A	C	B	B
 2 | C	D	D	A
 3 | A	C	D	D
 4 | A	B	C	B
 5 | B	B	B	C
 6 | A	C	D	B
 7 | B	B	B	D
 8 | A	D	B	B
 9 | C	C	C	C
10 | D	B	C	D
11 | C	A	C	D
12 | A	D	C	C
13 | B	D	D	C
14 | C	D	B	B
15 | A	D	C	D
16 | D	D	D	C
17 | B	C	D	C
18 | A	C	B	C
19 | B	D	B	B
20 | D	D	D	A
21 | C	C	A	B
22 | B	C	C	A
23 | C	C	B	A
24 | C	B	B	C
25 | A	D	A	B
26 | B	C	D	D
27 | C	A	B	D
28 | C	B	C	B
29 | C	B	A	C
30 | B	B	C	D
31 | 


--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
 1 | # Files generated by protoc
 2 | mctest_pb2.py
 3 | 
 4 | *.py[cod]
 5 | 
 6 | # C extensions
 7 | *.so
 8 | 
 9 | # Packages
10 | *.egg
11 | *.egg-info
12 | dist
13 | build
14 | eggs
15 | parts
16 | bin
17 | var
18 | sdist
19 | develop-eggs
20 | .installed.cfg
21 | lib
22 | lib64
23 | __pycache__
24 | 
25 | # Installer logs
26 | pip-log.txt
27 | 
28 | # Unit test / coverage reports
29 | .coverage
30 | .tox
31 | nosetests.xml
32 | 
33 | # Translations
34 | *.mo
35 | 
36 | # Mr Developer
37 | .mr.developer.cfg
38 | .project
39 | .pydevproject
40 | 


--------------------------------------------------------------------------------
/data/MCTest/mc500.dev.ans:
--------------------------------------------------------------------------------
 1 | A	A	C	B
 2 | B	A	A	C
 3 | A	B	B	A
 4 | C	C	A	C
 5 | A	A	A	A
 6 | A	C	B	C
 7 | C	B	B	C
 8 | D	A	A	A
 9 | B	B	D	C
10 | C	D	A	A
11 | C	C	C	D
12 | A	B	D	C
13 | B	C	C	D
14 | B	C	C	C
15 | A	D	A	B
16 | B	C	A	D
17 | A	C	D	B
18 | D	A	A	D
19 | A	C	C	C
20 | C	C	A	B
21 | D	D	B	C
22 | B	D	C	C
23 | A	B	C	A
24 | D	D	D	A
25 | B	C	C	B
26 | C	A	B	C
27 | D	C	D	B
28 | D	B	D	C
29 | A	D	C	B
30 | A	D	B	D
31 | C	C	D	C
32 | B	C	B	A
33 | B	D	D	A
34 | C	A	B	B
35 | D	A	D	C
36 | C	A	A	D
37 | C	D	D	A
38 | A	A	A	B
39 | B	D	A	D
40 | A	B	C	B
41 | D	A	D	D
42 | A	C	C	B
43 | B	B	C	D
44 | A	C	B	C
45 | A	B	D	B
46 | B	D	A	A
47 | B	A	C	C
48 | B	B	B	C
49 | A	B	B	B
50 | A	A	B	A
51 | 


--------------------------------------------------------------------------------
/data/MCTestAnswers/mc160.test.ans:
--------------------------------------------------------------------------------
 1 | A	A	B	B
 2 | D	B	C	B
 3 | C	A	B	D
 4 | C	D	B	C
 5 | C	C	A	A
 6 | A	B	D	D
 7 | B	D	B	B
 8 | A	B	D	D
 9 | C	A	B	A
10 | C	A	D	C
11 | B	C	D	B
12 | B	B	D	A
13 | A	D	B	A
14 | D	A	C	D
15 | D	D	C	B
16 | B	C	B	A
17 | A	C	D	D
18 | C	C	C	D
19 | B	B	C	C
20 | C	B	D	B
21 | A	D	A	B
22 | C	B	A	B
23 | B	A	D	C
24 | B	B	B	D
25 | A	C	D	C
26 | C	C	A	A
27 | B	A	B	D
28 | C	B	D	A
29 | A	C	C	A
30 | B	A	B	B
31 | D	B	D	D
32 | C	B	B	D
33 | C	A	D	C
34 | C	B	D	A
35 | A	C	D	A
36 | C	D	C	A
37 | B	B	B	D
38 | B	C	C	D
39 | D	A	A	A
40 | C	D	B	D
41 | C	C	D	A
42 | C	C	B	B
43 | C	C	C	C
44 | B	C	A	D
45 | C	C	C	B
46 | A	B	A	B
47 | A	D	A	B
48 | A	B	A	D
49 | A	D	C	C
50 | C	C	A	D
51 | D	A	C	C
52 | C	C	A	D
53 | C	B	B	D
54 | A	D	C	D
55 | D	D	B	B
56 | C	A	D	B
57 | D	D	A	A
58 | A	D	A	C
59 | D	A	C	B
60 | C	D	C	A
61 | 


--------------------------------------------------------------------------------
/data/MCTest/mc160.train.ans:
--------------------------------------------------------------------------------
 1 | C	D	B	C
 2 | D	A	D	C
 3 | A	C	B	A
 4 | D	A	C	D
 5 | A	D	B	B
 6 | D	D	A	C
 7 | D	C	A	B
 8 | B	C	B	B
 9 | A	D	D	C
10 | D	D	D	C
11 | A	D	A	D
12 | C	C	B	B
13 | D	C	D	B
14 | A	B	C	C
15 | A	A	A	C
16 | A	D	B	B
17 | D	B	A	D
18 | A	A	A	D
19 | D	B	A	A
20 | D	C	A	C
21 | A	D	B	A
22 | C	C	A	B
23 | C	D	A	D
24 | A	B	C	A
25 | D	A	D	C
26 | B	B	C	C
27 | C	A	A	C
28 | C	D	C	A
29 | A	C	A	B
30 | D	B	B	B
31 | B	A	C	A
32 | B	D	D	A
33 | B	C	D	C
34 | A	C	C	C
35 | D	B	C	D
36 | C	B	A	B
37 | D	B	B	B
38 | C	C	C	B
39 | A	C	C	A
40 | C	D	B	A
41 | A	B	C	A
42 | A	C	A	B
43 | C	B	D	C
44 | B	A	D	D
45 | B	C	B	A
46 | A	B	A	A
47 | D	A	B	B
48 | D	C	B	C
49 | C	B	A	C
50 | D	C	D	C
51 | A	B	B	D
52 | C	C	C	A
53 | B	B	D	B
54 | D	B	D	C
55 | C	C	D	B
56 | C	C	D	C
57 | D	A	C	D
58 | A	B	B	A
59 | A	A	B	A
60 | B	A	A	A
61 | C	C	C	C
62 | C	B	C	D
63 | D	B	C	C
64 | C	D	D	B
65 | D	D	A	B
66 | A	A	A	C
67 | C	D	C	D
68 | A	B	C	C
69 | C	C	B	C
70 | A	A	D	D
71 | 


--------------------------------------------------------------------------------
/mctest.proto:
--------------------------------------------------------------------------------
 1 | package mctest;
 2 | 
 3 | 
 4 | // Representation of stories using word tokens:
 5 | 
 6 | message AnswerAsWords {
 7 |     repeated string tokens = 1;
 8 | }
 9 | 
10 | message QuestionAsWords {
11 |     enum Type {
12 |         ONE = 1;
13 |         MULTIPLE = 2;
14 |     }
15 |     required Type type = 1;
16 |     repeated string tokens = 2;
17 |     repeated AnswerAsWords answers = 3;
18 | }
19 | 
20 | message StoryAsWords {
21 |     required string id = 1;
22 |     required string description = 2;
23 |     // Content fields:
24 |     repeated string passage = 3;
25 |     repeated QuestionAsWords questions = 4;
26 | }
27 | 
28 | 
29 | // Representation of stories using embeddings:
30 | 
31 | message Vector {
32 |     repeated double value = 1;
33 | }
34 | 
35 | message AnswerAsEmbeddings {
36 |     repeated Vector tokens = 1;
37 | }
38 | 
39 | message QuestionAsEmbeddings {
40 |     enum Type {
41 |         ONE = 1;
42 |         MULTIPLE = 2;
43 |     }
44 |     required Type type = 1;
45 |     repeated Vector tokens = 2;
46 |     repeated AnswerAsEmbeddings answers = 3;
47 | }
48 | 
49 | message StoryAsEmbeddings {
50 |     required string id = 1;
51 |     required string description = 2;
52 |     // Content fields:
53 |     repeated Vector passage = 3;
54 |     repeated QuestionAsEmbeddings questions = 4;
55 | }
56 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | MCTest Dataset
 2 | ========
 3 | 
 4 | Baseline models as well as more complex ones for doing question answering on the MCTest dataset.
 5 | 
 6 | Dependencies:
 7 | ```
 8 | protobuf
 9 | numpy
10 | pandas
11 | nltk
12 | ```
13 | 
14 | Word embeddings can be used from a model file created by [word2vec](https://github.com/danielfrg/word2vec).
15 | 
16 | ## Running baseline models
17 | 
18 | 
19 | First, clone the repo and compile the protobuf:
20 | ```
21 | git clone https://github.com/mcobzarenco/mctest.git 
22 | cd mctest
23 | protoc --python_out=. mctest.proto
24 | ```
25 | 
26 | To parse the raw data (dev + train combined), remove stopwords and save it as a length delimted protobuf flat file:
27 | ```
28 | cat data/MCTest/mc160.dev.tsv data/MCTest/mc160.train.tsv | \
29 |   ./parse.py --rm-stop data/stopwords.txt -o proto > train160-stop.words
30 | ```
31 | 
32 | Also create a file with the ground truth for dev + train:
33 | ```
34 | cat data/MCTest/mc160.dev.ans data/MCTest/mc160.train.ans > train160.ans 
35 | ```
36 | 
37 | To run the sliding window with distance baseline:
38 | ```
39 | ./baseline.py --train train160-stop.words --truth train160.ans --distance
40 | 
41 | [model]
42 | window_size = None
43 | distance = True
44 | 
45 | [results]
46 | All accuracy [400]: 0.5600
47 | Single accuracy [185]: 0.5946
48 | Multiple accuracy [215]: 0.5302
49 | ```
50 | 
51 | #### Word embeddings
52 | First, [word2vec](https://github.com/danielfrg/word2vec) should be installed and a model file with embeddings created.
53 | Say the model file is `mctest.vec.bin`, the following command will parse the raw data (dev + train combined), replace the words with their corresponding embedding and save that to disk:
54 | ```
55 | cat data/MCTest/mc160.dev.tsv data/MCTest/mc160.train.tsv | \
56 |   ./parse.py --model-file mctest.vec.bin --rm-punct -o proto > train160-punct-mctest.embed
57 | ```
58 | To run the sliding window model over the embeddings:
59 | ```
60 | ./baseline-embed.py --train train160-punct-mctest.embed --truth train160.ans 
61 | 
62 | [model]
63 | window_size = None
64 | 
65 | All accuracy [400]: 0.5775
66 | Single accuracy [185]: 0.6108
67 | Multiple accuracy [215]: 0.5488
68 | ```
69 | 


--------------------------------------------------------------------------------
/data/MCTestAnswers/mc500.test.ans:
--------------------------------------------------------------------------------
  1 | D	C	C	B
  2 | A	B	A	D
  3 | B	C	A	D
  4 | B	D	D	C
  5 | D	C	A	B
  6 | B	A	B	C
  7 | D	A	A	D
  8 | B	D	A	A
  9 | D	B	D	D
 10 | D	D	B	A
 11 | A	A	D	B
 12 | D	A	B	A
 13 | C	A	D	D
 14 | B	B	D	B
 15 | C	C	C	D
 16 | C	D	C	B
 17 | B	A	D	C
 18 | B	A	A	B
 19 | D	B	B	C
 20 | C	B	C	D
 21 | D	A	B	B
 22 | A	C	D	C
 23 | B	B	D	A
 24 | C	D	B	B
 25 | D	B	A	D
 26 | B	C	C	A
 27 | C	B	C	D
 28 | D	A	C	D
 29 | B	B	B	A
 30 | A	D	A	C
 31 | B	B	B	C
 32 | A	A	B	A
 33 | C	D	D	A
 34 | A	D	D	A
 35 | B	D	D	A
 36 | A	C	D	D
 37 | B	A	C	D
 38 | C	A	C	A
 39 | B	D	A	C
 40 | C	C	C	D
 41 | C	D	C	D
 42 | D	C	B	C
 43 | D	D	C	D
 44 | B	B	A	C
 45 | A	A	B	D
 46 | B	C	C	A
 47 | D	D	D	D
 48 | C	A	C	D
 49 | C	D	B	B
 50 | C	A	A	D
 51 | A	A	D	D
 52 | C	A	C	C
 53 | B	B	C	C
 54 | A	A	A	B
 55 | C	B	A	B
 56 | B	B	A	C
 57 | C	D	A	D
 58 | C	A	C	C
 59 | D	C	D	B
 60 | A	C	B	A
 61 | A	C	B	A
 62 | D	C	D	A
 63 | C	C	D	C
 64 | A	C	D	B
 65 | C	C	D	B
 66 | A	B	B	A
 67 | B	C	D	A
 68 | D	B	B	D
 69 | C	C	D	B
 70 | A	D	B	C
 71 | D	C	D	C
 72 | A	D	C	B
 73 | A	B	C	D
 74 | A	D	D	B
 75 | B	A	A	A
 76 | A	D	A	C
 77 | C	B	D	D
 78 | D	C	A	D
 79 | B	D	A	A
 80 | D	D	C	D
 81 | A	B	A	B
 82 | B	D	B	C
 83 | D	B	D	A
 84 | C	C	D	C
 85 | B	A	D	B
 86 | A	A	B	A
 87 | D	D	B	C
 88 | A	D	D	B
 89 | B	C	D	B
 90 | B	B	A	A
 91 | D	C	D	D
 92 | A	B	C	C
 93 | B	A	D	A
 94 | C	D	B	D
 95 | C	A	C	B
 96 | A	C	D	B
 97 | A	B	D	D
 98 | C	A	B	A
 99 | B	B	B	D
100 | D	B	B	A
101 | D	D	D	D
102 | D	B	C	D
103 | D	D	C	D
104 | C	C	B	B
105 | D	C	A	A
106 | C	A	D	C
107 | C	C	A	B
108 | B	D	D	D
109 | A	D	A	A
110 | D	A	D	A
111 | A	A	C	A
112 | C	C	B	A
113 | C	B	B	A
114 | B	D	A	A
115 | D	A	C	D
116 | B	B	D	B
117 | A	B	D	B
118 | A	D	C	C
119 | C	B	D	B
120 | C	B	C	C
121 | B	B	C	D
122 | D	B	D	A
123 | D	A	B	C
124 | C	D	D	B
125 | C	D	B	C
126 | A	A	B	B
127 | A	C	A	D
128 | D	C	B	B
129 | A	B	A	A
130 | B	A	A	A
131 | D	C	D	D
132 | C	C	D	A
133 | C	D	A	B
134 | A	D	C	C
135 | D	C	D	A
136 | C	B	B	A
137 | A	B	A	C
138 | D	B	D	C
139 | C	D	B	B
140 | D	C	B	B
141 | D	D	C	B
142 | C	D	A	D
143 | C	C	D	D
144 | A	C	B	D
145 | D	B	B	C
146 | C	C	C	D
147 | B	A	C	B
148 | C	B	A	B
149 | C	A	A	B
150 | A	D	D	D
151 | 


--------------------------------------------------------------------------------
/data/MCTest/mc500.train.ans:
--------------------------------------------------------------------------------
  1 | B	C	C	D
  2 | B	D	D	B
  3 | D	D	D	B
  4 | A	B	C	C
  5 | C	C	D	A
  6 | C	C	A	C
  7 | A	B	C	C
  8 | D	C	C	A
  9 | A	B	D	D
 10 | A	A	C	A
 11 | B	B	D	B
 12 | C	D	B	D
 13 | B	D	A	B
 14 | B	B	C	A
 15 | A	B	C	C
 16 | D	D	D	A
 17 | B	B	C	D
 18 | B	D	C	D
 19 | D	C	D	B
 20 | D	B	A	A
 21 | D	D	B	C
 22 | B	C	C	A
 23 | B	A	D	D
 24 | D	A	D	A
 25 | B	C	D	B
 26 | B	D	D	A
 27 | D	B	C	A
 28 | C	A	C	D
 29 | A	C	B	C
 30 | D	C	B	D
 31 | A	C	B	C
 32 | A	B	D	B
 33 | C	C	C	D
 34 | D	C	A	C
 35 | B	C	D	A
 36 | C	A	D	D
 37 | D	A	A	B
 38 | B	A	D	B
 39 | C	C	B	A
 40 | C	B	B	A
 41 | A	B	A	D
 42 | B	D	D	B
 43 | D	A	B	C
 44 | A	C	D	C
 45 | C	A	D	B
 46 | D	D	B	B
 47 | C	D	D	B
 48 | A	D	D	B
 49 | C	A	D	C
 50 | D	A	C	D
 51 | C	B	B	A
 52 | A	D	D	D
 53 | C	D	D	A
 54 | D	D	D	B
 55 | B	B	B	D
 56 | D	C	A	C
 57 | B	C	D	B
 58 | A	D	B	A
 59 | C	B	A	D
 60 | A	A	C	D
 61 | B	C	C	D
 62 | A	D	D	C
 63 | B	A	C	C
 64 | C	B	B	B
 65 | D	A	A	B
 66 | C	A	C	A
 67 | A	B	D	D
 68 | B	D	B	C
 69 | A	A	C	D
 70 | C	A	A	D
 71 | C	C	A	C
 72 | A	C	D	A
 73 | D	C	C	A
 74 | B	D	C	B
 75 | D	A	B	B
 76 | B	B	C	D
 77 | D	A	D	C
 78 | C	B	B	C
 79 | C	D	D	D
 80 | C	B	A	B
 81 | D	A	A	C
 82 | A	D	A	A
 83 | B	C	D	C
 84 | B	A	A	A
 85 | A	D	C	B
 86 | C	B	B	A
 87 | C	B	D	B
 88 | C	B	B	C
 89 | D	C	D	A
 90 | B	C	C	B
 91 | C	B	D	A
 92 | B	D	B	D
 93 | D	D	C	D
 94 | B	D	B	A
 95 | D	B	D	B
 96 | B	B	C	D
 97 | C	C	D	C
 98 | A	C	A	B
 99 | C	C	A	B
100 | D	C	C	C
101 | A	B	B	B
102 | D	C	A	A
103 | D	B	C	A
104 | A	B	C	C
105 | B	D	D	A
106 | A	A	A	D
107 | C	D	A	B
108 | A	A	C	B
109 | C	D	A	C
110 | C	B	B	C
111 | D	C	D	D
112 | A	A	B	A
113 | C	D	B	C
114 | C	C	D	B
115 | C	C	A	D
116 | B	A	D	B
117 | D	B	B	C
118 | A	B	D	D
119 | D	C	D	D
120 | C	A	A	B
121 | D	B	C	C
122 | C	D	D	C
123 | B	A	A	A
124 | D	C	A	A
125 | C	C	A	A
126 | D	B	D	C
127 | C	C	B	C
128 | B	C	C	B
129 | D	C	A	A
130 | C	B	A	D
131 | B	D	B	D
132 | A	A	A	D
133 | D	D	C	B
134 | D	A	D	C
135 | C	D	A	A
136 | A	C	D	B
137 | A	B	A	A
138 | A	B	C	C
139 | C	D	C	B
140 | D	D	A	B
141 | D	D	D	B
142 | D	A	D	A
143 | D	C	A	B
144 | D	D	C	B
145 | D	D	C	B
146 | A	D	A	B
147 | C	D	A	D
148 | C	B	B	B
149 | C	D	D	D
150 | C	C	A	C
151 | A	B	A	C
152 | D	B	C	B
153 | B	D	C	B
154 | A	D	C	B
155 | D	D	B	A
156 | C	B	C	B
157 | D	A	B	D
158 | D	D	C	D
159 | B	D	B	D
160 | D	A	B	A
161 | C	D	D	B
162 | C	D	A	D
163 | B	A	B	D
164 | A	D	B	C
165 | B	A	A	A
166 | B	D	A	B
167 | A	A	B	A
168 | A	C	A	D
169 | B	D	D	D
170 | A	D	B	A
171 | A	C	B	C
172 | D	A	D	D
173 | C	A	A	D
174 | C	D	B	A
175 | C	D	C	A
176 | A	B	D	A
177 | B	D	A	B
178 | A	A	C	C
179 | A	A	A	A
180 | D	C	C	C
181 | C	B	B	B
182 | D	D	D	D
183 | D	B	C	C
184 | C	A	C	D
185 | C	D	A	D
186 | D	D	C	B
187 | B	B	C	A
188 | D	D	B	A
189 | C	A	B	C
190 | A	B	C	D
191 | C	D	B	B
192 | A	A	B	A
193 | C	D	C	B
194 | A	B	C	D
195 | A	A	B	B
196 | A	D	A	A
197 | B	D	A	C
198 | C	C	C	C
199 | B	A	A	A
200 | C	C	D	C
201 | C	D	D	A
202 | D	C	B	B
203 | C	C	D	A
204 | A	C	D	A
205 | D	D	D	B
206 | C	B	A	D
207 | C	A	A	B
208 | B	B	D	D
209 | B	D	C	A
210 | B	A	D	C
211 | A	C	D	D
212 | D	B	C	B
213 | D	D	D	C
214 | B	A	B	A
215 | C	A	A	D
216 | C	B	D	A
217 | D	B	A	A
218 | D	C	C	D
219 | C	D	A	A
220 | B	D	C	D
221 | C	C	A	A
222 | A	D	D	D
223 | A	A	B	C
224 | C	D	C	C
225 | A	C	A	B
226 | B	D	A	C
227 | D	C	C	C
228 | C	C	D	D
229 | B	A	D	B
230 | B	B	A	B
231 | C	C	B	B
232 | A	B	B	B
233 | C	B	C	A
234 | A	D	C	C
235 | D	A	D	D
236 | A	D	C	C
237 | D	B	D	D
238 | B	C	B	D
239 | D	A	C	C
240 | B	D	C	B
241 | B	C	D	D
242 | A	C	A	B
243 | A	D	B	A
244 | C	D	D	B
245 | A	C	C	D
246 | A	C	B	D
247 | D	D	B	B
248 | B	A	A	A
249 | D	C	B	D
250 | D	B	C	D
251 | B	B	C	A
252 | C	A	D	A
253 | C	A	A	B
254 | D	D	C	D
255 | D	A	D	B
256 | C	B	D	A
257 | C	D	C	B
258 | B	B	D	D
259 | A	D	C	C
260 | A	C	A	C
261 | C	A	A	D
262 | A	B	B	B
263 | B	D	C	C
264 | C	A	A	A
265 | A	B	A	A
266 | B	C	A	C
267 | D	C	C	C
268 | A	A	A	D
269 | B	B	A	B
270 | D	B	D	B
271 | D	C	C	D
272 | B	C	B	D
273 | D	B	B	D
274 | B	C	D	D
275 | B	C	A	A
276 | A	A	A	C
277 | D	A	C	B
278 | A	A	D	A
279 | B	D	B	A
280 | B	C	A	A
281 | C	C	B	B
282 | B	B	A	C
283 | A	A	A	C
284 | B	B	A	D
285 | A	B	D	D
286 | B	B	C	D
287 | C	C	A	B
288 | C	D	C	C
289 | D	C	A	D
290 | D	A	B	A
291 | B	C	A	A
292 | D	C	C	C
293 | D	B	D	B
294 | C	B	C	C
295 | B	D	B	A
296 | D	D	A	A
297 | C	B	A	D
298 | C	D	A	B
299 | C	A	B	D
300 | A	D	C	D
301 | 


--------------------------------------------------------------------------------
/baseline-embed.py:
--------------------------------------------------------------------------------
  1 | #!/usr/bin/env python
  2 | # -*- coding: utf-8 -*-
  3 | from __future__ import print_function, division
  4 | import argparse
  5 | import json
  6 | import os
  7 | import struct
  8 | import sys
  9 | from base64 import urlsafe_b64decode as b64decode, \
 10 |     urlsafe_b64encode as b64encode
 11 | from collections import defaultdict
 12 | from functools import partial
 13 | from itertools import imap
 14 | 
 15 | import numpy as np
 16 | 
 17 | from mctest_pb2 import StoryAsEmbeddings, QuestionAsEmbeddings
 18 | from parse import parse_proto_stream
 19 | 
 20 | 
 21 | ANSWER_LETTER = ['A', 'B', 'C', 'D']
 22 | 
 23 | 
 24 | def load_target_answers(stream):
 25 |     answers = stream.readlines()
 26 |     answers = map(lambda x: x.rstrip().split('\t'), answers)
 27 |     return reduce(lambda x, y: x + y, answers)
 28 | 
 29 | 
 30 | def l2_normalize(v):
 31 |     return v / np.sqrt(np.dot(v, v))
 32 | 
 33 | 
 34 | class SlidingWindowEmbeddings(object):
 35 |     def __init__(self, window_size=None):
 36 |         self._window_size = window_size
 37 | 
 38 |     def score_target(self, passage, target, verbose=True):
 39 |         target_size = len(target)
 40 |         window_size = self._window_size or target_size
 41 |         mean_target = l2_normalize(np.mean(target, 0))
 42 |         max_score = -np.inf
 43 |         tokens_at_max = []
 44 |         for i in xrange(len(passage) - window_size):
 45 |             try:
 46 |                 mean_passage = l2_normalize(
 47 |                     np.mean(passage[i:i + window_size], 0))
 48 |                 score = -np.dot(mean_passage-mean_target, mean_passage-mean_target)
 49 |                 if score > max_score:
 50 |                     max_score = score
 51 |                     tokens_at_max = i, i + window_size
 52 |             except IndexError:
 53 |                 pass
 54 |         if verbose:
 55 |             print('[score=%.2f] passage: %s ' %
 56 |                   (max_score, tokens_at_max), file=sys.stderr)
 57 |         return max_score
 58 | 
 59 |     def predict(self, passage, question, answers, verbose=True):
 60 |         scores = []
 61 |         for answer in answers:
 62 |             scores.append(self.score_target(
 63 |                 passage, question + answer, verbose))
 64 |         return scores
 65 | 
 66 | 
 67 | def tokens_to_embeddings(model, tokens):
 68 |     embeds = []
 69 |     for token in tokens:
 70 |         try:
 71 |             token = token.lower()
 72 |             embeds.append(model[token])
 73 |         except KeyError as e:
 74 |             print('WARNING: "%s" missing from vocabulary.' % token,
 75 |                   file=sys.stderr)
 76 |     return embeds
 77 | 
 78 | 
 79 | if __name__ == '__main__':
 80 |     parser = argparse.ArgumentParser(
 81 |         description='Baseline models from the MCTest paper (sliding '
 82 |         'window and distance based)')
 83 |     _arg = parser.add_argument
 84 |     _arg('--train', type=str, action='store', metavar='FILE', required=True,
 85 |          help='File with stories and questions (JSON format).')
 86 |     _arg('--truth', type=str, action='store', metavar='FILE',
 87 |          help='File with correct answers to the questions.')
 88 |     _arg('--window-size', type=int, action='store', metavar='SIZE',
 89 |          default=None, help='Fixed window size for the sliding window ' \
 90 |          'algorithm. By default it has the same length as the question.')
 91 |     args = parser.parse_args()
 92 | 
 93 |     stories = list(parse_proto_stream(open(args.train, 'r'), StoryAsEmbeddings))
 94 |     print('[model]\nwindow_size = %s\n' % (args.window_size))
 95 | 
 96 |     sw = SlidingWindowEmbeddings(window_size=args.window_size)
 97 |     predicted, q_types = [], []
 98 |     to_array_list = lambda tokens: map(lambda s: np.array(s.value), tokens)
 99 |     for story in stories[:]:
100 |         passage_vec = to_array_list(story.passage)
101 |         for question in story.questions:
102 |             q_types.append(question.type)
103 |             question_vec = to_array_list(question.tokens)
104 |             answers_vec = [to_array_list(answer.tokens)
105 |                            for answer in question.answers]
106 |             scores = sw.predict(passage_vec, question_vec, answers_vec, False)
107 |             # print(ANSWER_LETTER[scores.index(max(scores))])
108 |             predicted.append(ANSWER_LETTER[scores.index(max(scores))])
109 | 
110 |     if args.truth:
111 |         answers_in = open(args.truth, 'r')
112 |         answers = np.array(load_target_answers(answers_in))
113 |         predicted = np.array(predicted)
114 |         assert len(answers) == len(predicted)
115 | 
116 |         single = np.array(q_types) == QuestionAsEmbeddings.ONE
117 |         n_single = float(np.sum(single))
118 |         n_multiple = float(np.sum(~single))
119 |         assert n_single + n_multiple == len(answers)
120 | 
121 |         print('All accuracy [%d]: %.4f' %
122 |               (n_single + n_multiple,
123 |                np.sum(answers == predicted) / float(len(predicted))))
124 |         print('Single accuracy [%d]: %.4f' %
125 |               (n_single,
126 |                np.sum(answers[single] == predicted[single]) / n_single))
127 |         print('Multiple accuracy [%d]: %.4f\n' %
128 |               (n_multiple,
129 |                np.sum(answers[~single] == predicted[~single]) / n_multiple))
130 |     else:
131 |         for p in predicted:
132 |             print(p, file=sys.stdout)
133 | 


--------------------------------------------------------------------------------
/baseline.py:
--------------------------------------------------------------------------------
  1 | #!/usr/bin/env python
  2 | # -*- coding: utf-8 -*-
  3 | from __future__ import print_function, division
  4 | import argparse
  5 | import json
  6 | import os
  7 | import struct
  8 | import sys
  9 | from base64 import urlsafe_b64decode as b64decode, \
 10 |     urlsafe_b64encode as b64encode
 11 | from collections import defaultdict
 12 | from functools import partial
 13 | from itertools import imap
 14 | 
 15 | import numpy as np
 16 | 
 17 | from mctest_pb2 import StoryAsWords, QuestionAsWords
 18 | from parse import parse_proto_stream
 19 | 
 20 | 
 21 | ANSWER_LETTER = ['A', 'B', 'C', 'D']
 22 | 
 23 | 
 24 | def compute_counts(stories):
 25 |     counts = defaultdict(lambda: 0.0)
 26 |     for story in stories:
 27 |         for token in story.passage:
 28 |             counts[token] += 1.0
 29 |     return counts
 30 | 
 31 | 
 32 | def compute_inverse_counts(stories):
 33 |     counts = compute_counts(stories)
 34 |     icounts = {}
 35 |     for token, token_count in counts.iteritems():
 36 |         icounts[token] = np.log(1.0 + 1.0 / token_count)
 37 |     return icounts
 38 | 
 39 | 
 40 | def baseline_distance(passage, question, answer):
 41 |     if not isinstance(question, set):
 42 |         question = set(question)
 43 |     if not isinstance(answer, set):
 44 |         answer = set(answer)
 45 |     s_question = question.intersection(passage)
 46 |     s_answer = answer.intersection(passage).difference(question)
 47 |     if len(s_question) == 0 or len(s_answer) == 0:
 48 |         return 1.0
 49 |     last_q, last_a = np.inf, np.inf
 50 |     closest = np.inf
 51 |     for i, token in enumerate(passage):
 52 |         if token in s_question:
 53 |             last_q = i
 54 |         if token in s_answer:
 55 |             last_a = i
 56 |         if abs(last_q - last_a) < closest:
 57 |             # print(last_q, last_a)
 58 |             closest = np.abs(last_q - last_a) / (len(passage) - 1)
 59 |     assert closest > 0 and closest <= 1
 60 |     return closest
 61 | 
 62 | 
 63 | class SlidingWindow(object):
 64 |     def __init__(self):
 65 |         pass
 66 | 
 67 |     def fit(self, stories, window_size=None):
 68 |         self._icounts = compute_inverse_counts(stories)
 69 |         self._window_size = window_size
 70 | 
 71 |     def predict_target(self, tokens, target, verbose=True):
 72 |         if not isinstance(target, set):
 73 |             target = set(target)
 74 |         target_size = len(target)
 75 |         max_overlap_score = 0.0
 76 |         tokens_at_max = []
 77 |         for i in xrange(len(tokens)):
 78 |             overlap_score = 0.0
 79 |             try:
 80 |                 window_size = self._window_size or target_size
 81 |                 for j in xrange(window_size):
 82 |                     if tokens[i + j] in target:
 83 |                         overlap_score += self._icounts[tokens[i + j]]
 84 |             except IndexError:
 85 |                 pass
 86 |             if overlap_score > max_overlap_score:
 87 |                 tokens_at_max = tokens[i:i + window_size]
 88 |                 max_overlap_score = overlap_score
 89 |         if verbose:
 90 |             print('[score=%.2f for target=%s] passage: %s ' %
 91 |                   (max_overlap_score, target, tokens_at_max), file=sys.stderr)
 92 |         return max_overlap_score
 93 | 
 94 |     def predict(self, passage, question, answers,
 95 |                 with_distance=True, verbose=True):
 96 |         scores = []
 97 |         if verbose:
 98 |             print('Question: %s' % question)
 99 |         for answer in answers:
100 |             dist = baseline_distance(passage, question, answer) \
101 |                    if with_distance else 0
102 |             scores.append(self.predict_target(
103 |                 passage, set(question + answer), verbose) - dist)
104 |         return scores
105 | 
106 | 
107 | def load_target_answers(stream):
108 |     answers = stream.readlines()
109 |     answers = map(lambda x: x.rstrip().split('\t'), answers)
110 |     return reduce(lambda x, y: x + y, answers)
111 | 
112 | 
113 | if __name__ == '__main__':
114 |     parser = argparse.ArgumentParser(
115 |         description='Baseline models from the MCTest paper (sliding '
116 |         'window and distance based)')
117 |     _arg = parser.add_argument
118 |     _arg('--train', type=str, action='store', metavar='FILE', required=True,
119 |          help='File with stories and questions (JSON format).')
120 |     _arg('--truth', type=str, action='store', metavar='FILE',
121 |          help='File with correct answers to the questions.')
122 |     _arg('--window-size', type=int, action='store', metavar='SIZE',
123 |          default=None, help='Fixed window size for the sliding window ' \
124 |          'algorithm. By default it has the same length as the question.')
125 |     _arg('--distance', action='store_true',
126 |          help='Substract the baseline distance measure.')
127 |     args = parser.parse_args()
128 | 
129 |     stories = list(parse_proto_stream(open(args.train, 'r')))
130 |     print('[model]\nwindow_size = %s\ndistance = %s\n' %
131 |           (args.window_size, args.distance))
132 | 
133 |     sw = SlidingWindow()
134 |     sw.fit(stories, window_size=args.window_size)
135 |     predicted, q_types = [], []
136 |     for story in stories:
137 |         passage = story.passage
138 |         for question in story.questions:
139 |             q_types.append(question.type)
140 |             answer_tokens = map(lambda x: list(x.tokens), question.answers)
141 |             scores = sw.predict(passage, list(question.tokens), answer_tokens,
142 |                                 with_distance=args.distance, verbose=False)
143 |             predicted_letter = ANSWER_LETTER[scores.index(max(scores))]
144 |             # print('scores: %s (%s)' % (scores, predicted_letter))
145 |             predicted.append(predicted_letter)
146 | 
147 |     if args.truth:
148 |         answers_in = open(args.truth, 'r')
149 |         answers = np.array(load_target_answers(answers_in))
150 |         predicted = np.array(predicted)
151 |         assert len(answers) == len(predicted)
152 | 
153 |         single = np.array(q_types) == QuestionAsWords.ONE
154 |         n_single = float(np.sum(single))
155 |         n_multiple = float(np.sum(~single))
156 |         assert n_single + n_multiple == len(answers)
157 | 
158 |         print('[results]')
159 |         print('All accuracy [%d]: %.4f' %
160 |               (n_single + n_multiple,
161 |                np.sum(answers == predicted) / float(len(predicted))))
162 |         print('Single accuracy [%d]: %.4f' %
163 |               (n_single,
164 |                np.sum(answers[single] == predicted[single]) / n_single))
165 |         print('Multiple accuracy [%d]: %.4f' %
166 |               (n_multiple,
167 |                np.sum(answers[~single] == predicted[~single]) / n_multiple))
168 |     else:
169 |         for p in predicted:
170 |             print(p, file=sys.stdout)
171 | 


--------------------------------------------------------------------------------
/data/stopwords.txt:
--------------------------------------------------------------------------------
  1 | a
  2 | a's
  3 | able
  4 | about
  5 | above
  6 | according
  7 | accordingly
  8 | across
  9 | actually
 10 | after
 11 | afterwards
 12 | again
 13 | against
 14 | ain't
 15 | all
 16 | allow
 17 | allows
 18 | almost
 19 | alone
 20 | along
 21 | already
 22 | also
 23 | although
 24 | always
 25 | am
 26 | among
 27 | amongst
 28 | an
 29 | and
 30 | another
 31 | any
 32 | anybody
 33 | anyhow
 34 | anyone
 35 | anything
 36 | anyway
 37 | anyways
 38 | anywhere
 39 | apart
 40 | appear
 41 | appreciate
 42 | appropriate
 43 | are
 44 | aren't
 45 | around
 46 | as
 47 | aside
 48 | ask
 49 | asking
 50 | associated
 51 | at
 52 | available
 53 | away
 54 | awfully
 55 | b
 56 | be
 57 | became
 58 | because
 59 | become
 60 | becomes
 61 | becoming
 62 | been
 63 | before
 64 | beforehand
 65 | behind
 66 | being
 67 | believe
 68 | below
 69 | beside
 70 | besides
 71 | best
 72 | better
 73 | between
 74 | beyond
 75 | both
 76 | brief
 77 | but
 78 | by
 79 | c
 80 | c'mon
 81 | c's
 82 | came
 83 | can
 84 | can't
 85 | cannot
 86 | cant
 87 | cause
 88 | causes
 89 | certain
 90 | certainly
 91 | changes
 92 | clearly
 93 | co
 94 | com
 95 | come
 96 | comes
 97 | concerning
 98 | consequently
 99 | consider
100 | considering
101 | contain
102 | containing
103 | contains
104 | corresponding
105 | could
106 | couldn't
107 | course
108 | currently
109 | d
110 | definitely
111 | described
112 | despite
113 | did
114 | didn't
115 | different
116 | do
117 | does
118 | doesn't
119 | doing
120 | don't
121 | done
122 | down
123 | downwards
124 | during
125 | e
126 | each
127 | edu
128 | eg
129 | eight
130 | either
131 | else
132 | elsewhere
133 | enough
134 | entirely
135 | especially
136 | et
137 | etc
138 | even
139 | ever
140 | every
141 | everybody
142 | everyone
143 | everything
144 | everywhere
145 | ex
146 | exactly
147 | example
148 | except
149 | f
150 | far
151 | few
152 | fifth
153 | first
154 | five
155 | followed
156 | following
157 | follows
158 | for
159 | former
160 | formerly
161 | forth
162 | four
163 | from
164 | further
165 | furthermore
166 | g
167 | get
168 | gets
169 | getting
170 | given
171 | gives
172 | go
173 | goes
174 | going
175 | gone
176 | got
177 | gotten
178 | greetings
179 | h
180 | had
181 | hadn't
182 | happens
183 | hardly
184 | has
185 | hasn't
186 | have
187 | haven't
188 | having
189 | he
190 | he's
191 | hello
192 | help
193 | hence
194 | her
195 | here
196 | here's
197 | hereafter
198 | hereby
199 | herein
200 | hereupon
201 | hers
202 | herself
203 | hi
204 | him
205 | himself
206 | his
207 | hither
208 | hopefully
209 | how
210 | howbeit
211 | however
212 | i
213 | i'd
214 | i'll
215 | i'm
216 | i've
217 | ie
218 | if
219 | ignored
220 | immediate
221 | in
222 | inasmuch
223 | inc
224 | indeed
225 | indicate
226 | indicated
227 | indicates
228 | inner
229 | insofar
230 | instead
231 | into
232 | inward
233 | is
234 | isn't
235 | it
236 | it'd
237 | it'll
238 | it's
239 | its
240 | itself
241 | j
242 | just
243 | k
244 | keep
245 | keeps
246 | kept
247 | know
248 | knows
249 | known
250 | l
251 | last
252 | lately
253 | later
254 | latter
255 | latterly
256 | least
257 | less
258 | lest
259 | let
260 | let's
261 | like
262 | liked
263 | likely
264 | little
265 | look
266 | looking
267 | looks
268 | ltd
269 | m
270 | mainly
271 | many
272 | may
273 | maybe
274 | me
275 | mean
276 | meanwhile
277 | merely
278 | might
279 | more
280 | moreover
281 | most
282 | mostly
283 | much
284 | must
285 | my
286 | myself
287 | n
288 | name
289 | namely
290 | nd
291 | near
292 | nearly
293 | necessary
294 | need
295 | needs
296 | neither
297 | never
298 | nevertheless
299 | new
300 | next
301 | nine
302 | no
303 | nobody
304 | non
305 | none
306 | noone
307 | nor
308 | normally
309 | not
310 | nothing
311 | novel
312 | now
313 | nowhere
314 | o
315 | obviously
316 | of
317 | off
318 | often
319 | oh
320 | ok
321 | okay
322 | old
323 | on
324 | once
325 | one
326 | ones
327 | only
328 | onto
329 | or
330 | other
331 | others
332 | otherwise
333 | ought
334 | our
335 | ours
336 | ourselves
337 | out
338 | outside
339 | over
340 | overall
341 | own
342 | p
343 | particular
344 | particularly
345 | per
346 | perhaps
347 | placed
348 | please
349 | plus
350 | possible
351 | presumably
352 | probably
353 | provides
354 | q
355 | que
356 | quite
357 | qv
358 | r
359 | rather
360 | rd
361 | re
362 | really
363 | reasonably
364 | regarding
365 | regardless
366 | regards
367 | relatively
368 | respectively
369 | right
370 | s
371 | said
372 | same
373 | saw
374 | say
375 | saying
376 | says
377 | second
378 | secondly
379 | see
380 | seeing
381 | seem
382 | seemed
383 | seeming
384 | seems
385 | seen
386 | self
387 | selves
388 | sensible
389 | sent
390 | serious
391 | seriously
392 | seven
393 | several
394 | shall
395 | she
396 | should
397 | shouldn't
398 | since
399 | six
400 | so
401 | some
402 | somebody
403 | somehow
404 | someone
405 | something
406 | sometime
407 | sometimes
408 | somewhat
409 | somewhere
410 | soon
411 | sorry
412 | specified
413 | specify
414 | specifying
415 | still
416 | sub
417 | such
418 | sup
419 | sure
420 | t
421 | t's
422 | take
423 | taken
424 | tell
425 | tends
426 | th
427 | than
428 | thank
429 | thanks
430 | thanx
431 | that
432 | that's
433 | thats
434 | the
435 | their
436 | theirs
437 | them
438 | themselves
439 | then
440 | thence
441 | there
442 | there's
443 | thereafter
444 | thereby
445 | therefore
446 | therein
447 | theres
448 | thereupon
449 | these
450 | they
451 | they'd
452 | they'll
453 | they're
454 | they've
455 | think
456 | third
457 | this
458 | thorough
459 | thoroughly
460 | those
461 | though
462 | three
463 | through
464 | throughout
465 | thru
466 | thus
467 | to
468 | together
469 | too
470 | took
471 | toward
472 | towards
473 | tried
474 | tries
475 | truly
476 | try
477 | trying
478 | twice
479 | two
480 | u
481 | un
482 | under
483 | unfortunately
484 | unless
485 | unlikely
486 | until
487 | unto
488 | up
489 | upon
490 | us
491 | use
492 | used
493 | useful
494 | uses
495 | using
496 | usually
497 | uucp
498 | v
499 | value
500 | various
501 | very
502 | via
503 | viz
504 | vs
505 | w
506 | want
507 | wants
508 | was
509 | wasn't
510 | way
511 | we
512 | we'd
513 | we'll
514 | we're
515 | we've
516 | welcome
517 | well
518 | went
519 | were
520 | weren't
521 | what
522 | what's
523 | whatever
524 | when
525 | whence
526 | whenever
527 | where
528 | where's
529 | whereafter
530 | whereas
531 | whereby
532 | wherein
533 | whereupon
534 | wherever
535 | whether
536 | which
537 | while
538 | whither
539 | who
540 | who's
541 | whoever
542 | whole
543 | whom
544 | whose
545 | why
546 | will
547 | willing
548 | wish
549 | with
550 | within
551 | without
552 | won't
553 | wonder
554 | would
555 | would
556 | wouldn't
557 | x
558 | y
559 | yes
560 | yet
561 | you
562 | you'd
563 | you'll
564 | you're
565 | you've
566 | your
567 | yours
568 | yourself
569 | yourselves
570 | z
571 | zero
572 | ,
573 | ?
574 | ;
575 | _
576 | $
577 | 's
578 | .
579 | -LRB-
580 | -RRB-
581 | "
582 | '
583 | :
584 | !
585 | ``
586 | ''
587 | 


--------------------------------------------------------------------------------
/data/MCTest/README.txt:
--------------------------------------------------------------------------------
  1 | MCTest: Machine comprehension test
  2 | http://research.microsoft.com/mct
  3 | 
  4 | ---------------------------------------
  5 | Welcome
  6 | ---------------------------------------
  7 | 
  8 | In this archive, you'll find the 660 reading comprehension 
  9 | tests (split into MC160 and MC500) as described in this paper:
 10 | 
 11 | Matthew Richardson, Christopher J.C. Burges, and Erin Renshaw (2013).  
 12 | "MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of
 13 | Text," in Proceedings of the 2013 Conference on Emprical Methods in Natural 
 14 | Language Processing (EMNLP 2013), pp. 193-203, Seattle, WA, USA, October 2013.
 15 | http://research.microsoft.com/en-us/um/redmond/projects/mctest/MCTest_EMNLP2013.pdf
 16 | 
 17 | If you use this data, we ask that you reference the above paper so that 
 18 | others may also easily find and use the data themselves. If you have any
 19 | questions or find the data useful, please don't hesitate to contact us:
 20 |  
 21 |   Matt Richardson: mattri@microsoft.com
 22 |   Chris Burges:    cburges@microsoft.com
 23 |   Erin Renshaw:    erinren@microsoft.com
 24 |   
 25 | ---------------------------------------
 26 | Train, Development, and Test sets
 27 | ---------------------------------------
 28 | 
 29 | There are two primary datasets: mc500 and mc160. See our paper (link above)
 30 | for a description of the differences between these two sets. MC500 contains
 31 | 500 story sets (a story set is a story and its associated questions); MC160
 32 | contains 160.
 33 | 
 34 | Each dataset is split into train, development, and test sets, with each
 35 | story set assigned to one. As one would expect, the train set can be used 
 36 | to train your algorithm, or to examine closely to see what kind of phenomenon
 37 | exist in the stories, or any other purpose you would like to use it for. 
 38 | The development set is intended to be a set-aside set that you can use for
 39 | evaluating your algorithm. The test set is intended to be a final test set
 40 | that you use only once, to get your final results for publishing.
 41 | 
 42 | The answers for the test set are distributed in a separate archive. We 
 43 | encourage you to download this file only when you are ready to do your 
 44 | final evaluation. For both TSV and TXT format, downloading the answers
 45 | archive will allow you to use the same code as was used when evaluating
 46 | on the development set.
 47 | 
 48 | The files are named: mc[500|160].[train|dev|test].[txt|tsv|ans]
 49 |   
 50 | ---------------------------------------
 51 | License
 52 | ---------------------------------------
 53 | 
 54 | Please see the included license.pdf for the license
 55 | 
 56 | ---------------------------------------
 57 | Data Format
 58 | ---------------------------------------
 59 | 
 60 | We provide the data into two separate formats: .txt for ease of 
 61 | readability, and .tsv/.ans for ease of coding. The two formats contain 
 62 | the same information, just in different formats.
 63 | 
 64 | In both formats, questions are prefixed with "one:" or "multiple:", 
 65 | indicating whether the author marked that the question required one or 
 66 | multiple sentences from the story in order to find the right answer.
 67 | 
 68 | The text in the stories has been processed as little as possible to remain
 69 | true to the original author's submission. Special non-ASCII characters such
 70 | as curly quotation marks, em-dashes, and elipses have been converted to 
 71 | their ASCII equivalent. 
 72 | 
 73 | ---- TXT Format ----
 74 | 
 75 | The .txt files present the stories and questions in a convenient text 
 76 | format, for ease of reading. The correct answer for each question is marked 
 77 | with a "*". The format is consistent, so can be programmatically read if 
 78 | desired, but may be harder to write a parser for than the TSV format.
 79 | Note that the test story sets do not indicate the correct answer (see 
 80 | not above on train/dev/test split). To get the test sets in text format
 81 | that do contain the answer, you must download the test answers archive.
 82 | 
 83 | ---- TSV/ANS Format ----
 84 | 
 85 | These consist of tab-delimited files, with one story set per line. 
 86 | The .tsv file contains the story, questions, and answers.
 87 | The .ans file contains the correct answer for each question
 88 | 
 89 | The format of a line in the TSV file is:
 90 |   Id <tab> properties <tab> story <tab> q1 <tab> q2 <tab> q3 <tab> q4 
 91 |     where
 92 |   qN = questionText <tab> answerA <tab> answerB <tab> answerC <tab> answerD
 93 |     and
 94 |   properties is a semicolon-delimited list of property:value pairs, including
 95 |     Author (anonymized author id, consistent across all files)
 96 |     Work Time(s): Seconds between author accepting and submitting the task
 97 |     Qual. score: The author's grammar qualification test score (% correct)
 98 |     Creativity Words: Words the author was given to encourage creativity
 99 |     (there are no creativity words or qual score for mc160, see paper)
100 | 
101 | The format of a line in the ANS file is:
102 |   answer1 <tab> answer2 <tab> answer3 <tab> answer4
103 |     where
104 |   answerN is the correct answer (A, B, C, or D) for question N
105 | 
106 | Finally, because some authors used newlines and/or tabs to indicate
107 | paragraph separation, and this would break the TSV format, we have
108 | replaced any newline or tab with "\newline" or "\tab", respectively.
109 | No questions or answers required this escaping.
110 | 
111 | ---------------------------------------
112 | An Ongoing Resource
113 | ---------------------------------------
114 | 
115 | As we stated in our paper, we will maintain the website with links
116 | to the latest published results using this data. If you publish a paper
117 | using this data, let us know and we will add a link to it.
118 | 
119 | Also, if you publish a paper and are willing to share your scoring
120 | files with others, send them to us and we will post them as well. We
121 | hope that by providing the scoring files from previous work, we will
122 | enable more rapid progress on this problem -- by enabling each new
123 | algorithm to build on top of previous algorithmic results, by 
124 | allowing pairwise statistical significance testing, and by allowing 
125 | anyone to investigate what kind of errors are being made by previous
126 | work.
127 | 
128 | ---------------------------------------
129 | Score Files
130 | ---------------------------------------
131 | 
132 | To send us your scores, please format them in the following tab-delimited
133 | format, one line per story (similar to the ANS file):
134 | 
135 |   scores1 <tab> scores2 <tab> scores3 <tab> scores4 <tab>
136 |     where
137 |   scoresN are the scores for question N, and have the format:
138 |   scoresN = scoreN_A, scoreN_B, scoreN_C, scoreN_D
139 |   where scoreN_A is the score your algo assigns to answer A for question N.
140 | 
141 | The scores may be probabilities, or may simply be unnormalized real values. 
142 | It is assumed that the highest score is the one your algorithm would select,
143 | and the higher the score, the more confident it is in that selection.
144 | 
145 | example:
146 |   3.2, 1.1, 0.9, 3.1 <tab> -0.3, 1.1, -4.3, 0.4 <tab> ...
147 | would mean the algorithm selects "A" for question 1, and "B" for question 2.
148 |   
149 | We will provide these score files for public download, attributed to you and
150 | with a link to your publication if possible. 
151 | 
152 | 


--------------------------------------------------------------------------------
/data/MCTestAnswers/README.txt:
--------------------------------------------------------------------------------
  1 | MCTest: Machine comprehension test
  2 | http://research.microsoft.com/mct
  3 | 
  4 | ---------------------------------------
  5 | Welcome
  6 | ---------------------------------------
  7 | 
  8 | In this archive, you'll find the 660 reading comprehension 
  9 | tests (split into MC160 and MC500) as described in this paper:
 10 | 
 11 | Matthew Richardson, Christopher J.C. Burges, and Erin Renshaw (2013).  
 12 | "MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of
 13 | Text," in Proceedings of the 2013 Conference on Emprical Methods in Natural 
 14 | Language Processing (EMNLP 2013), pp. 193-203, Seattle, WA, USA, October 2013.
 15 | http://research.microsoft.com/en-us/um/redmond/projects/mctest/MCTest_EMNLP2013.pdf
 16 | 
 17 | If you use this data, we ask that you reference the above paper so that 
 18 | others may also easily find and use the data themselves. If you have any
 19 | questions or find the data useful, please don't hesitate to contact us:
 20 |  
 21 |   Matt Richardson: mattri@microsoft.com
 22 |   Chris Burges:    cburges@microsoft.com
 23 |   Erin Renshaw:    erinren@microsoft.com
 24 |   
 25 | ---------------------------------------
 26 | Train, Development, and Test sets
 27 | ---------------------------------------
 28 | 
 29 | There are two primary datasets: mc500 and mc160. See our paper (link above)
 30 | for a description of the differences between these two sets. MC500 contains
 31 | 500 story sets (a story set is a story and its associated questions); MC160
 32 | contains 160.
 33 | 
 34 | Each dataset is split into train, development, and test sets, with each
 35 | story set assigned to one. As one would expect, the train set can be used 
 36 | to train your algorithm, or to examine closely to see what kind of phenomenon
 37 | exist in the stories, or any other purpose you would like to use it for. 
 38 | The development set is intended to be a set-aside set that you can use for
 39 | evaluating your algorithm. The test set is intended to be a final test set
 40 | that you use only once, to get your final results for publishing.
 41 | 
 42 | The answers for the test set are distributed in a separate archive. We 
 43 | encourage you to download this file only when you are ready to do your 
 44 | final evaluation. For both TSV and TXT format, downloading the answers
 45 | archive will allow you to use the same code as was used when evaluating
 46 | on the development set.
 47 | 
 48 | The files are named: mc[500|160].[train|dev|test].[txt|tsv|ans]
 49 |   
 50 | ---------------------------------------
 51 | License
 52 | ---------------------------------------
 53 | 
 54 | Please see the included license.pdf for the license
 55 | 
 56 | ---------------------------------------
 57 | Data Format
 58 | ---------------------------------------
 59 | 
 60 | We provide the data into two separate formats: .txt for ease of 
 61 | readability, and .tsv/.ans for ease of coding. The two formats contain 
 62 | the same information, just in different formats.
 63 | 
 64 | In both formats, questions are prefixed with "one:" or "multiple:", 
 65 | indicating whether the author marked that the question required one or 
 66 | multiple sentences from the story in order to find the right answer.
 67 | 
 68 | The text in the stories has been processed as little as possible to remain
 69 | true to the original author's submission. Special non-ASCII characters such
 70 | as curly quotation marks, em-dashes, and elipses have been converted to 
 71 | their ASCII equivalent. 
 72 | 
 73 | ---- TXT Format ----
 74 | 
 75 | The .txt files present the stories and questions in a convenient text 
 76 | format, for ease of reading. The correct answer for each question is marked 
 77 | with a "*". The format is consistent, so can be programmatically read if 
 78 | desired, but may be harder to write a parser for than the TSV format.
 79 | Note that the test story sets do not indicate the correct answer (see 
 80 | not above on train/dev/test split). To get the test sets in text format
 81 | that do contain the answer, you must download the test answers archive.
 82 | 
 83 | ---- TSV/ANS Format ----
 84 | 
 85 | These consist of tab-delimited files, with one story set per line. 
 86 | The .tsv file contains the story, questions, and answers.
 87 | The .ans file contains the correct answer for each question
 88 | 
 89 | The format of a line in the TSV file is:
 90 |   Id <tab> properties <tab> story <tab> q1 <tab> q2 <tab> q3 <tab> q4 
 91 |     where
 92 |   qN = questionText <tab> answerA <tab> answerB <tab> answerC <tab> answerD
 93 |     and
 94 |   properties is a semicolon-delimited list of property:value pairs, including
 95 |     Author (anonymized author id, consistent across all files)
 96 |     Work Time(s): Seconds between author accepting and submitting the task
 97 |     Qual. score: The author's grammar qualification test score (% correct)
 98 |     Creativity Words: Words the author was given to encourage creativity
 99 |     (there are no creativity words or qual score for mc160, see paper)
100 | 
101 | The format of a line in the ANS file is:
102 |   answer1 <tab> answer2 <tab> answer3 <tab> answer4
103 |     where
104 |   answerN is the correct answer (A, B, C, or D) for question N
105 | 
106 | Finally, because some authors used newlines and/or tabs to indicate
107 | paragraph separation, and this would break the TSV format, we have
108 | replaced any newline or tab with "\newline" or "\tab", respectively.
109 | No questions or answers required this escaping.
110 | 
111 | ---------------------------------------
112 | An Ongoing Resource
113 | ---------------------------------------
114 | 
115 | As we stated in our paper, we will maintain the website with links
116 | to the latest published results using this data. If you publish a paper
117 | using this data, let us know and we will add a link to it.
118 | 
119 | Also, if you publish a paper and are willing to share your scoring
120 | files with others, send them to us and we will post them as well. We
121 | hope that by providing the scoring files from previous work, we will
122 | enable more rapid progress on this problem -- by enabling each new
123 | algorithm to build on top of previous algorithmic results, by 
124 | allowing pairwise statistical significance testing, and by allowing 
125 | anyone to investigate what kind of errors are being made by previous
126 | work.
127 | 
128 | ---------------------------------------
129 | Score Files
130 | ---------------------------------------
131 | 
132 | To send us your scores, please format them in the following tab-delimited
133 | format, one line per story (similar to the ANS file):
134 | 
135 |   scores1 <tab> scores2 <tab> scores3 <tab> scores4 <tab>
136 |     where
137 |   scoresN are the scores for question N, and have the format:
138 |   scoresN = scoreN_A, scoreN_B, scoreN_C, scoreN_D
139 |   where scoreN_A is the score your algo assigns to answer A for question N.
140 | 
141 | The scores may be probabilities, or may simply be unnormalized real values. 
142 | It is assumed that the highest score is the one your algorithm would select,
143 | and the higher the score, the more confident it is in that selection.
144 | 
145 | example:
146 |   3.2, 1.1, 0.9, 3.1 <tab> -0.3, 1.1, -4.3, 0.4 <tab> ...
147 | would mean the algorithm selects "A" for question 1, and "B" for question 2.
148 |   
149 | We will provide these score files for public download, attributed to you and
150 | with a link to your publication if possible. 
151 | 
152 | 


--------------------------------------------------------------------------------
/parse.py:
--------------------------------------------------------------------------------
  1 | #!/usr/bin/env python
  2 | # -*- coding: utf-8 -*-
  3 | from __future__ import print_function, division
  4 | import argparse
  5 | import json
  6 | import errno
  7 | import os
  8 | import struct
  9 | import sys
 10 | from base64 import urlsafe_b64decode as b64decode, \
 11 |     urlsafe_b64encode as b64encode
 12 | from functools import partial
 13 | from itertools import imap, ifilter
 14 | 
 15 | import nltk
 16 | import pandas as pd
 17 | from google.protobuf import text_format
 18 | 
 19 | from mctest_pb2 import AnswerAsWords, QuestionAsWords, StoryAsWords, \
 20 |     AnswerAsEmbeddings, QuestionAsEmbeddings, StoryAsEmbeddings
 21 | 
 22 | 
 23 | DEFAULT_OUTPUT_FORMAT = 'json'
 24 | 
 25 | COLUMNS = ['id', 'description', 'story',
 26 |            'q1', 'a11', 'a12', 'a13', 'a14',
 27 |            'q2', 'a21', 'a22', 'a23', 'a24',
 28 |            'q3', 'a31', 'a32', 'a33', 'a34',
 29 |            'q4', 'a41', 'a42', 'a43', 'a44']
 30 | QUESTION_TYPES = ['one', 'multiple']
 31 | 
 32 | PUNCTS = ['.', '?', ',', '!', '"', '\'', '$', '%', '^', '&']
 33 | 
 34 | 
 35 | def question_text(question):
 36 |     return question.split(':')[1].strip()
 37 | 
 38 | 
 39 | def question_type(question):
 40 |     question_type, _ = question.split(':')
 41 |     assert question_type in QUESTION_TYPES
 42 |     return question_type
 43 | 
 44 | 
 45 | def row_to_dict(row, tokenize=None):
 46 |     return {
 47 |         'id': row['id'],
 48 |         'description': row['description'],
 49 |         'passage': tokenize(row['story']),
 50 |         'questions': [{
 51 |             'tokens': tokenize(question_text(row['q%d' % q_number])),
 52 |             'answers': [tokenize(row['a%d%d' % (q_number, a_number)])
 53 |                         for a_number in xrange(1, 5)],
 54 |             'type': question_type(row['q%d' % q_number])
 55 |         } for q_number in xrange(1, 5)]
 56 |     }
 57 | 
 58 | 
 59 | def datapoint_to_tokens(datapoint, include_answers=False):
 60 |     tokens = datapoint['passage']
 61 |     for question in datapoint['questions']:
 62 |         tokens.extend(question['tokens'])
 63 |         if include_answers:
 64 |             for answer in datapoint['answers']:
 65 |                 tokens.extend(answer)
 66 |     return ' '.join(map(lambda t: t.lower(), tokens))
 67 | 
 68 | 
 69 | def datapoint_to_proto_as_words(datapoint):
 70 |     story = StoryAsWords()
 71 |     story.id = datapoint['id']
 72 |     story.description = datapoint['description']
 73 |     story.passage.extend(datapoint['passage'])
 74 |     for question_dict in datapoint['questions']:
 75 |         question = story.questions.add()
 76 |         if question_dict['type'] == 'one':
 77 |             question.type = QuestionAsWords.ONE
 78 |         elif question_dict['type'] == 'multiple':
 79 |             question.type = QuestionAsWords.MULTIPLE
 80 |         else:
 81 |             print('Invalid question type: %s' % question_dict['type'],
 82 |                   file=sys.stderr)
 83 |             sys.exit(3)
 84 |         question.tokens.extend(question_dict['tokens'])
 85 |         for answer_list in question_dict['answers']:
 86 |             answer = question.answers.add()
 87 |             answer.tokens.extend(answer_list)
 88 |     return story
 89 | 
 90 | 
 91 | def datapoint_to_proto_as_embeddings(datapoint):
 92 |     story = StoryAsEmbeddings()
 93 |     story.id = datapoint['id']
 94 |     story.description = datapoint['description']
 95 |     for passage_vec in datapoint['passage']:
 96 |         embed = story.passage.add()
 97 |         embed.value.extend(list(passage_vec))
 98 |     for question_dict in datapoint['questions']:
 99 |         question = story.questions.add()
100 |         if question_dict['type'] == 'one':
101 |             question.type = QuestionAsWords.ONE
102 |         elif question_dict['type'] == 'multiple':
103 |             question.type = QuestionAsWords.MULTIPLE
104 |         else:
105 |             print('Invalid question type: %s' % question_dict['type'],
106 |                   file=sys.stderr)
107 |             sys.exit(3)
108 |         for token_vec in question_dict['tokens']:
109 |             question.tokens.add().value.extend(list(token_vec))
110 |         for answer_list in question_dict['answers']:
111 |             answer = question.answers.add()
112 |             for answer_vec in answer_list:
113 |                 answer.tokens.add().value.extend(list(answer_vec))
114 |     return story
115 | 
116 | 
117 | def length_prefix_proto(proto):
118 |     serialized = proto.SerializeToString()
119 |     return struct.pack('I', len(serialized)) + serialized
120 | 
121 | 
122 | def parse_proto_stream(stream, proto_type=StoryAsWords):
123 |     while True:
124 |         proto_size_bin = stream.read(4)
125 |         if len(proto_size_bin) != 4:
126 |             if len(proto_size_bin) == 0:
127 |                 return
128 |             print('Invalid read: rubbish at the end of the file?',
129 |                   file=sys.stderr)
130 |             return
131 |         proto_size = struct.unpack_from('I', proto_size_bin)[0]
132 |         story = proto_type()
133 |         story.ParseFromString(stream.read(proto_size))
134 |         yield story
135 | 
136 | 
137 | if __name__ == '__main__':
138 |     parser = argparse.ArgumentParser(
139 |         description='Converts raw TSV files from the MCTest dataset')
140 |     _arg = parser.add_argument
141 |     _arg('-o', type=str, action='store', metavar='FORMAT',
142 |          default=DEFAULT_OUTPUT_FORMAT,
143 |          help='Output format: json, proto, proto_text, token_list (default=%s)' %
144 |          DEFAULT_OUTPUT_FORMAT)
145 |     _arg('--rm-stop', type=str, action='store', metavar='FILE',
146 |          help='Remove stop words specified by file (one word per line).')
147 |     _arg('--rm-punct', action='store_true',
148 |          help='Remove punctuation when tokenizing.')
149 |     _arg('--model-file', type=str, action='store', metavar='FILE', default=None,
150 |          help='File with word2vec model. If provided, makes it output' \
151 |          'embeddings.')
152 |     _arg('-i', type=str, action='store', metavar='FILE', default=None,
153 |          help='Input file (TSV).')
154 |     args = parser.parse_args()
155 | 
156 |     token_mappers = []
157 | 
158 |     if args.rm_stop:
159 |         stopwords = open(args.rm_stop, 'r').read().split('\n')
160 |         stopwords = set(map(lambda x: x.strip().rstrip(), stopwords))
161 |         token_mappers.append(lambda x: x if x.lower() not in stopwords else None)
162 | 
163 |     if args.rm_punct:
164 |         token_mappers.append(lambda x: x if x not in PUNCTS else None)
165 | 
166 |     as_embeddings = args.model_file is not None
167 |     if args.model_file:
168 |         import word2vec
169 |         embedding_model = word2vec.load(args.model_file)
170 |         def to_embeddings(token):
171 |             try:
172 |                 return embedding_model[token.lower()]
173 |             except KeyError as e:
174 |                 print('WARNING: "%s" missing from vocabulary.' % token.lower(),
175 |                       file=sys.stderr)
176 |             return None
177 |         token_mappers.append(to_embeddings)
178 | 
179 |     def tokenize(text):
180 |         if not isinstance(text, basestring):
181 |             text = str(text)
182 |         text = text.replace('\\newline', ' ')
183 |         mapped = nltk.word_tokenize(text)
184 |         for mapper in token_mappers:
185 |             mapped = filter(lambda x: x is not None, map(mapper, mapped))
186 |         return mapped
187 | 
188 |     data_in = open(args.i, 'r') if args.i else sys.stdin
189 |     df = pd.read_csv(data_in, sep='\t', names=COLUMNS)
190 |     for row in (df.ix[i] for i in df.index):
191 |         datapoint = row_to_dict(row, tokenize)
192 |         try:
193 |             serialized = None
194 |             if args.o == 'json':
195 |                 serialized = json.dumps(datapoint) + '\n'
196 |             elif args.o == 'proto' or args.o == 'proto_text':
197 |                 proto = datapoint_to_proto_as_embeddings(datapoint) \
198 |                         if as_embeddings else \
199 |                            datapoint_to_proto_as_words(datapoint)
200 |                 serialized = length_prefix_proto(proto) if args.o == 'proto' \
201 |                              else text_format.MessageToString(proto)
202 |             elif args.o == 'token_list':
203 |                 serialized = datapoint_to_tokens(datapoint) + ' '
204 |             else:
205 |                 print('Unknown output format "%s"' % args.o,
206 |                       file=sys.stderr)
207 |                 sys.exit(2)
208 |             assert serialized
209 |             sys.stdout.write(serialized)
210 |         except IOError as e:
211 |             if e.errno == errno.EPIPE:
212 |                 sys.exit(0)
213 |             raise e
214 | 


--------------------------------------------------------------------------------
/data/MCTest/mc160.dev.tsv:
--------------------------------------------------------------------------------
 1 | mc160.dev.0	Author: 2670363255;Work Time(s): 1446	It was Jessie Bear's birthday. She was having a party.  She asked her two best friends to\newlinecome to the party.  She made a big cake, and hung up some balloons.\newline\newlineSoon her friend Lion came over. Then her friend Tiger came over. Lion and Tiger brought\newlinepresents with them.\newline\newlineJessie hugged her friends. She asked them if they would like to have cake. \newline\newlineYes! said Lion. Yes yes! said Tiger. Jessie cut the cake, and they all ate it together.\newlineThen Jessie opened her presents. She got a new jump rope and a fun game.  She asked Lion\newlineand Tiger to play the game with her.\newline\newlineThe friends played and played. They all had a good time. Soon it was time for the party to\newlinebe over.\newline\newlineLion and Tiger hugged Jessie and said goodbye to her.  Thanks for a great birthday! Jessie\newlineBear told her two best friends.	one: Who was having a birthday?	Jessie Bear	no one	Lion	Tiger	multiple: Who didn't come to the party?	Lion	Tiger	Snake	Jessie Bear	multiple: How did Jessie get ready for the party?	made cake and juice.	made cake and hung balloons.	made juice and cookies.	made juice and hung balloons.	one: How many friends came to Jessie's party?	one	two	six	four
 2 | mc160.dev.1	Author: 3466834307;Work Time(s): 879	Sally had a very exciting summer vacation. She went to summer camp for the first time. She\newlinemade friends with a girl named Tina. They shared a bunk bed in their cabin. Sally's\newlinefavorite activity was walking in the woods because she enjoyed nature. Tina liked arts and\newlinecrafts. Together, they made some art using leaves they found in the woods. Even after she\newlinefell in the water, Sally still enjoyed canoeing. She was sad when the camp was over, but\newlinepromised to keep in touch with her new friend.\newline\newlineSally went to the beach with her family in the summer as well. She loves the beach. Sally\newlinecollected shells and mailed some to her friend, Tina, so she could make some arts and\newlinecrafts with them. Sally liked fishing with her brothers, cooking on the grill with her dad,\newlineand swimming in the ocean with her mother.\newline\newlineThe summer was fun, but Sally was very excited to go back to school. She missed her\newlinefriends and teachers. She was excited to tell them about her summer vacation.	multiple: Who went to the beach with Sally?	her sisters	Tina	her brothers, mother, and father	herself	multiple: What did Sally promise to do?	Learn to ride a bike.	Go to a baseball game.	Go back to the beach.	Keep in touch with her new friend, Tina.	one: Why does Sally like walking in the woods?	She likes to climb trees.	She likes to play hide and go seek.	She likes to swim.	She likes nature.	multiple: What did Sally do this summer?	She went to summer camp and the beach.	She went to Paris.	She went to a baseball game.	She went to summer school.
 3 | mc160.dev.2	Author: 519010308;Work Time(s): 1458	Todd lived in a town outside the city . Unlike the city the town was peaceful and quiet\newlineand full of trees, flowers and animals.  One day his dad came in from work and said "Come\newlineon, son, I'm going to take you to the city." Todd was very exited so he put on his shoes\newlineand ran to the car.  When they got to the city Todd was very surprised there were so many\newlinecars and people, everyone seemed to be in a hurry. There were no trees, no flowers, and no\newlineanimals. Todd was so happy to get back home.  When his mom asked him about his trip to the\newlinecity Todd said,"There's no place like home."	multiple: Where did Todd visit?	The city	His mom	The town	The animals	multiple: What did Todd say when he got home from the city?	There were so many trees and flowers.	There were so many people in cars.	There's no place like home.	There were so many animals.	one: Where does Todd live?	The city	with his mom	with his dad	In a town.	multiple: What did Todd see when he got to the city?	lots of animals	his mom	lots of trees and flowers	lots of people and cars
 4 | mc160.dev.3	Author: 1077562726;Work Time(s): 4133	Greta ran to the corner with her older brother Tony.  He had money for the ice cream truck\newlinein his pocket and she was very happy. The ice cream truck had been parked at the curb\newlinewaiting for children for a very long time.  The ice cream truck driver thought that no\newlinemore children were coming to get ice cream so he started pulling away from the curb when\newlinethey got to the corner. They yelled.  They screamed, "Stop! Stop!" and jumped up and down\newlineon the side walk trying to get him to see them. The driver of the truck saw them, waved at\newlinethem and smiled, pulled back to the curb and opened his truck up so that they could see\newlineeverything that he had for sale.  They were so excited. They saw some new treats. Tony\newlinewanted to try something new. He got an ice cream sundae with chocolate ice cream and\newlinenuts. He almost got a snow cone. Greta looked at everything that the ice cream truck\newlinehad. She saw candy, ice cream cones, snow cones, and everything else. It all looked so\newlinegood. But after looking at everything, she wanted to get an ice cream sandwich. She got\newlinethe ice cream sandwich. She bit into it and smiled. It tasted so good. She felt so\newlinehappy. Her brother, Tony, was happy too. He bit into his ice cream cone sundae and\newlinegrinned.  They walked home with their ice cream and told their mom about how close they\newlinecame to not getting their ice cream at all. Their mom was happy that the truck had stopped\newlinefor them. She said that they were very lucky to have gotten to the curb before the ice\newlinecream truck left.	multiple: What did the driver of the ice cream truck do when Greta and Tony got to the corner?	He started pulling away from the curb.	He played the truck's jingle.	He stayed parked at the curb.	He almost got a snow cone.	multiple: What did the children do when they saw the ice cream truck driver pull away from the curb?	They ran out into the street after the iced cream truck.	They screamed, "Stop! Stop!".	They stood on the corner and cried.	They ate ice cream.	multiple: What did Tony and Greta get from the iced cream truck?	Tony got a snow cone. Greta got an ice cream sundae.	Tony got a snow cone. Greta got an iced cream cone with chocolate iced cream and nuts.	Tony got an ice cream sundae with chocolate ice cream and nuts.	Greta and Tony ice cream cones.	multiple: What did Greta and Tony do after they got their ice cream?	They walked to a friend's house and talked to his mother about what happened.	They bit into it.	They got in the truck.	They walked home and went outside in their back yard to play.
 5 | mc160.dev.4	Author: 2626224031;Work Time(s): 2199	My parents, Kelly and Kelley, said that it was that time of year to take a family\newlinevacation.  We've been to big ride parks that have hotels with large pools.  This year my\newlineparents wanted to do something different.  They wanted to take us all to Elk River Castle.\newline\newlineAfter lots of planning we hit the road for our trip.  My Brother Kelsey and I enjoyed the\newlinelong car ride there.\newline  \newlineOnce we arrive, the castle looked much bigger than we had imagined.  There was so much to\newlinesee and so much to do.  There was a swimming pool, movie theater and an elevator to take\newlineus from floor to floor.  What a magical place!  I was so excited because we had the whole\newlineplace to our family!\newline  \newlineWe spent our vacation playing around the huge castle and finding small mysterious places.\newlineThere was even a tiny room in the back of one of the closets.  My brother, Kelsey, and I\newlineplayed hide and go seek for hours, watched movies and swam until the sun went down.\newline\newlineIt was sad when our vacation finally came to an end but we made some amazing memories.\newlineWe'll never forget our trip to Elk River Castle!	one: What was my brother's name?	Kelly	Kelsey	Caden	Colby	one: Where did we go?	Hood River Castle	Elk River Castle	White Fish Castle	White Salmon Castle	multiple: What did the castle have?	A ball room	A movie theater	A gym	A hot tub	multiple: What did we do at the castle?	Played ball	Fished	Swam in the swimming pool	Ran in the woods
 6 | mc160.dev.5	Author: 3983187336;Work Time(s): 1622	Once upon a time there a little girl named Ana. Ana was a smart girl. Everyone in Ana's\newlineschool knew and liked her very much. She had a big dream of becoming spelling bee\newlinewinner. Ana studied very hard to be the best she could be at spelling. Ana's best friend\newlinewould help her study every day after school. By the time the spelling bee arrived Ana and\newlineher best friend were sure she would win. There were ten students in the spelling bee. This\newlinemade Ana very nervous, but when she looked out and saw her dad cheering her on she knew\newlineshe could do it. The spelling bee had five rounds and Ana made it through them all. She\newlinewas now in the finals. During the final round James, the boy she was in the finals with, was\newlinegiven a really hard word and he spelled it wrong. All Ana had to do was spell this last\newlineword and she would be the winner. Ana stepped to the microphone, thought really hard and\newlinespelled the word. She waited and finally her teacher said "That is correct". Ana had won\newlinethe spelling bee. Ana was so happy. She won a trophy. Ana also won a big yellow\newlineribbon. The whole school was also happy, and everyone clapped for her. The whole school\newlinewent outside. They had a picnic to celebrate Ana winning.	multiple: What made Ana very nervous?	The other ten students	Her best friend	The bright lights	The big stage	multiple: Where did the school have the picnic?	The gym	Ana's house	Outside	Ana's classroom	one: What was Ana's big dream?	Becoming a ballerina	Becoming a famous singer	Becoming class president	Becoming spelling bee winner	one: Who helped Ana study everyday?	Her dad	Her best friend	Her mom	Her sister
 7 | mc160.dev.6	Author: 1006609625;Work Time(s): 2342	Roger was a grasshopper. He loved to hop. He hopped everywhere by himself. One day when he\newlinewas hopping around he bumped into a frog sitting on a log. The frog told him his name was\newlineGilbert. Gilbert told Roger that it had been a long time since he bumped into\newlineanybody. Roger told him that since both grasshoppers and frogs like to jump they would\newlinemake great friends. The next day they were hopping through a field and they saw something\newlinevery strange.  In a pond they saw a spider floating on a lily pad. The spider was very sad\newlinebecause he did not have any friends. Roger and Gilbert asked him why he didn't have any\newlinefriends. The spider told them that everybody would scream and run away when they saw him.\newlineRoger and Gilbert told him that he didn't look scary to them and that he could come along\newlinewith them if he wanted. So Sam the spider said yes, and the three of them began a life\newlinetime friendship full of adventures.	multiple: What did Roger like to do?	Bump.	Hop.	Swim.	Float.	one: What was the spider sitting on in the pond?	branch	Lily pad	land	log	multiple: What character is not in the story?	spider	lady bug	grasshopper	frog	one: What was the spider's name?	Roger	Sarah	Gilbert	Sam
 8 | mc160.dev.7	Author: 259176131;Work Time(s): 882	The cute red ball rolled over to the blue ball and said hello. The blue ball was scared\newlineand went to cry to the green ball. The green ball laughed at the blue ball. Then the green\newlineball told the orange ball that blue ball was stupid. Most felt this was not good to do and\newlineso they punished the green ball by taking away all his air.\newline\newlineFrom that day on everyone saw the air-less green ball and knew that they could not do or\newlinesay any bad things. This is how the trouble started. The purple ball used the fear of\newlineeveryone to become the leader that they all feared. The purple ball was mean to\newlineeveryone. Until one day the red ball spoke up and got all the other colored balls together\newlineand they took the air from the purple ball and put it in the green ball. Sadly, the green\newlineball had been without air for too long and was dead.	multiple: What color ball was the third brought up in the story?	green	blue	red	purple	one: Which color ball became the leader?	green	blue	red	purple	multiple: What color of ball scared the blue ball?	purple	red	orange	green	one: At they end of the story, what was the state of the green ball.	cute	dead	fear	taking
 9 | mc160.dev.8	Author: 863905974;Work Time(s): 329	Sara wanted to play on a baseball team. She had never tried to swing a bat and hit a\newlinebaseball before. Her Dad gave her a bat and together they went to the park to\newlinepractice. Sara wondered if she could hit a ball. She wasn't sure if she would be any\newlinegood. She really wanted to play on a team and wear a real uniform. She couldn't wait to\newlineget to the park and test out her bat. When Sara and her Dad reached the park, Sara grabbed\newlinethe bat and stood a few steps away from her Dad. Sara waited as her Dad pitched the ball\newlineto her. Her heart was beating fast. She missed the first few pitches. She felt like\newlinequitting but kept trying. Soon she was hitting the ball very far. She was very happy and\newlineshe couldn't wait to sign up for a real team. Her Dad was very proud of her for not giving\newlineup.	multiple: Why was Sara practicing?	She wanted to show off	She didn't want to do her homework	She wanted to play on a team	She was bored	one: Who pitched the ball to Sara?	Her Mom	Her Sister	Her Dad	Her Brother	multiple: Why was Sara's Dad proud of her?	She didn't get dirty	She didn't break the bat	She didn't quit	She was better than her Dad	one: Where did Sara go to practice hitting the ball?	A stadium	Her yard	The park	Her bedroom
10 | mc160.dev.9	Author: 2311321761;Work Time(s): 634	Peter was a very sad puppy.  He had been inside of the pet store for a very long time.  In\newlinefact, he had been there for three months!  Peter had seen many other puppies find a\newlineperson; he began to wonder why he could not get one.  He thought that maybe his fur was\newlinenot pretty enough or maybe his bark was not loud enough.  He tried and tried to please\newlineevery person who came to the store, but they all picked smaller puppies.  However, one day\newlineall of this changed.  Sammie came into the store looking for a golden puppy.  She wanted a\newlinepuppy she could snuggle with.  It so happened that Peter was very sad and tired that day.\newlineSammie came to hold him.  Peter wanted to show off his bark, but he was too tired.  He\newlinefell right to sleep.  Sammie loved him at once and loved holding him in her arms.  Sammie\newlinetook Peter home that day, and they made lots of fun memories.	multiple: What did Peter want to do when Sammie came?	He wanted to show off his fur	He wanted to be beautiful	He wanted to snuggle with her	He wanted to show off his bark	one: Where was Peter?	Sad and tired	At the pet store	Home	At the park practicing his bark	multiple: What did Peter actually do when Sammie came?	Peter showed off his fur	Peter showed off his bark	Peter fell asleep	Peter wondered if he would be a good enough puppy	multiple: What kind of puppy did Sammie want?	A golden puppy that was small	A golden puppy with shiny fur	A puppy with a loud bark she could snuggle with	A golden puppy she could snuggle with
11 | mc160.dev.10	Author: 3842083771;Work Time(s): 4095	Luna the hawk wanted some socks. It was the middle of winter and sitting on tree branches\newlinemade her feet very cold. Luna hoped that her friends could help her find some socks. She\newlineflew to the old maple tree where Olive the owl lived.\newline\newline"Olive, may I please borrow a pair of your socks?" she asked.\newline\newlineOlive the owl looked surprised. "Luna, I have no use for socks because my legs and toes\newlinehave thick feathers. Go visit one of the animals that walk on four legs. They might have\newlineextra socks you could borrow."\newline\newlineLuna flew across the field and landed next to the icy creek. Rose the raccoon was teaching\newlineher six babies how to wash their paws. The water was very cold, but the babies were having\newlinefun.\newline\newline"Rose, my bare legs and bare toes are so cold, may I please borrow a pair of your socks?"\newlinebegged Luna.\newline\newlineRose laughed hard. "Silly Luna, I do not have socks. Look at my legs and feet. They are\newlinecovered with thick, warm fur. I'm sorry I cannot help you. Go visit the humans. Sometimes\newlineI tip over their garbage cans at night when I am looking for food. Once I saw a pair of\newlinesocks."\newline\newlineLuna was very afraid of humans. Her grandmother and mother had warned her about them. She\newlinewas told that some humans are mean and hurt hawks. Her feet were so cold that it was\newlinedifficult to grip tree branches. She became brave. She flew to the farmhouse on the big\newlinehill. When she landed on the roof, she could not believe her eyes. She saw socks! In late\newlineautumn, Henrietta the human had put laundry outside to dry and she had forgotten to bring\newlinein one tiny pair of socks. The socks were hanging on the clothesline by two wooden\newlinepins. Luna used her powerful beak to break the pins. She put on the socks and then flew\newlineback to her home in the huge tree. When she landed, her feet were warm and dry. Luna was\newlinevery happy.	one: Why did Olive the owl not have any socks?	She had given her socks to another friend.	All of her socks were in the dirty laundry.	She has thick feathers on her legs and toes.	She wore ski boots instead of socks.	multiple: Why was Luna afraid of humans?	Her grandmother and mother had told stories about mean humans hurting hawks.	Humans were large and scary-looking.	Humans put garbage in the hawks' nests.	Humans stole all of the hawks' food.	multiple: Which animal did Luna not visit?	Olive the owl	Rose the raccoon	Opal the otter	Henrietta the human	multiple: How could the baby raccoons play in the icy creek without hurting their paws?	Because their mother made sure they had warm mittens to keep their paws dry.	Because their mother taught them how to play in the water without getting cold.	Because their legs and feet are tough from tipping over garbage cans.	Because their legs and feet have a thick covering of fur that keeps them warm.
12 | mc160.dev.11	Author: 534571148;Work Time(s): 3659	Once upon a time a young boy and young girl set out on a trip to the beach. They packed a\newlinefew towels, an umbrella, a few beach chairs and a lunch cooler. They drove to the crowded\newlinebeach parking lot and spent almost an hour trying to find a parking spot. Once they found\newlinea spot they parked and began walking to the beach area. They found a nice spot with a good\newlineview of the water and set up their belongings. Once they sat down they began to enjoy a\newlinenice lunch on the beach. They watched the boats go by and people playing in the water. It\newlinewas a wonderful day and one they would always remember. Once they arrived home they\newlinesuddenly found out that they both had a pretty good sunburn. They both said that next time\newlinethey would use sun screen.	multiple: Was it a good day for the couple, and what did they find out when they got home?	It was a good day, and they found that they were sunburned	It was not a good day, and they found they were sunburned.	It was a good day, and they found they were late getting home	It was not a good day, and they found that they got a parking ticket	multiple: Where were the couple going and how did they get their?	The beach and by Bike	The park and by bike	The store and by car	The beach and by car	one: Besides boats what did the couple watch?	dolphins	people making sand castles	people playing in the water	children playing in the sand	one: It took the young couple how long to find a parking spot?	almost a half hour	only a short time	almost an hour	over an hour
13 | mc160.dev.12	Author: 212417544;Work Time(s): 998	Three little kids lived in a great big house with a great big cat and many places for a\newlinegreat big cat to hide.  Their great big cat was named Cowboy.  And Cowboy was not a very\newlinenice cat.  Cowboy liked to bite and chew and scratch a great many things.  When Cowboy was\newlinehappy, which was not very often, Cowboy liked to bite in to a blanket or soft toy and\newlinecarry it around in his mouth.  When Cowboy was hungry he liked to bite bright red tomatoes\newlineand suck out all the juice and seeds.  And when Cowboy was feeling mean he liked to hide.\newlineCowboy would hide, curled up tight in a ball under a blanket or behind a corner and wait\newlinefor one of the little kids to pass by.  When they did pass by Cowboy would jump at their\newlinefeet and try to bite and scratch them.  He did not know that what he was doing was not\newlinevery nice.  Cowboy was only a cat.  A great big cat that did not know any better.	one: What was the cat's name?	Tony	Cowboy	Cat	Chowder	one: What did Cowboy like to eat when he was hungry?	Cowboy liked to eat cat food.	Cowboy liked to eat toys.	Cowboy liked to eat blankets.	Cowboy liked to eat tomatoes.	multiple: When Cowboy felt mean he liked to...	run and hide.	chew on toys.	bite the blankets.	hide and jump.	multiple: Cowboy was a...	a tiny little cat.	a normal size cat.	great big cat.	a great big dog.
14 | mc160.dev.13	Author: 1460358657;Work Time(s): 867	On the first day of school, Mrs. Law asked all the students to write a story telling her\newlinewhat they did over the summer. She told the students that they were going to read them in\newlinefront of the class. This was going to help everyone get to know more about each other.\newline\newlineWhen all the students were done writing their stories, Anna raised her hand to read hers\newlinefirst. Mrs. Law smiled at Anna's excitement to share her story with the class. She told\newlineall the students to sit down and listen to Anna.\newline\newlineAnna started reading her story. All the other students quickly paid attention, as her\newlinestory was telling about her vacation to a park with lots of rides. Anna told them that she\newlinerode a huge ride called, "Superman," which was her favorite. After Anna finished reading\newlineher story, all the students clapped and said that they wished that they could hear\newlinemore. Anna told them to tell their mommies and daddies to take them to visit the rides\newlinenext summer.	multiple: Why did the students have to read their stories to the class?	to get to know who had the best summer	to get to know Mrs. Law	to help them get to know more about each other	to get to know who had the best mommy and daddy	one: What did the students have to write about?	the first day of school	Mrs. Law	Anna's summer vacation	what they did over the summer	multiple: Why did Mrs. Law smile at Anna?	because Anna told the class a joke	because she raised her hand to read her story first	because Anna laughed	because Anna rode a huge ride	one: What was the huge ride called that Anna told the class about?	Batman	Superman	there wasn't one	Jolly Green Giant
15 | mc160.dev.14	Author: 534571148;Work Time(s): 10766	This is a story about a bear and a wolf. The bear met the wolf one day in the woods. The\newlinebear said to the wolf, would you like to go to the river with me? The wolf said yes, he\newlinewould like to go to the river. When the bear and the wolf got to the river they found that\newlinea beaver had built a bridge to the other side of the river. The bear and the wolf crossed\newlinethe bridge that was built by the beaver and found that they were now in a part of the\newlinewoods they had never seen before. A little worried that they may get lost in this part of\newlinethe woods they had never seen before the bear and the wolf turned around. They went back\newlineover the bridge and were happy to be back in a part of the woods they knew so well. The\newlinebeaver thanked both the bear and the wolf for trying out his new bridge and then started\newlineto build yet another bridge close to the first bridge. He was a very busy beaver.	one: Which animal built a bridge?	the beaver	the bear	the dog	the wolf	multiple: what did the bear and wolf cross, and why did they turn back?	a bridge, and they got hungry.	a lake, and they did not want to get lost.	a field and they did not want to get lost.	a bridge, and they did not want to get lost.	multiple: What did the beaver build and why did he thank the bear and wolf?	a bridge, and for helping him to build the bridge.	a house, and for trying out the bridge.	a bridge, and for trying out the bridge.	a bridge, and for bring him food	one: This is a story of which two animals taking a walk in the woods?	a bear and a beaver	a dog and a wolf	a bear and a dog	a bear and a wolf
16 | mc160.dev.15	Author: 3960091198;Work Time(s): 725	Jenny's family lived in a small apartment in Seattle.  One day Jenny came home from school\newlineand her mom told her that the family was moving to Utah.  Jenny was sad to leave her\newlinefriends. Jenny was sad to leave her school.  Jenny helped her mom pack boxes and clean\newlinetheir apartment to get ready for the move.  Soon the day came when Jenny's dad brought a\newlinelarge truck to the parking lot and all of the family's things were put inside.  Jenny and\newlineher mom rode in their car and her dad drove the truck towards Utah.  Jenny loved getting\newlineto eat lots of yummy fast food on the way.  When the family got to their new home in Utah,\newlineJenny helped her parents to take all of the boxes into the house.  She loved her new\newlinebedroom!  When Jenny was emptying box of her toys, there was a knock at the door.  It was\newlinea little girl who wanted Jenny to play! Jenny was going to like Utah!	one: Who drove the truck?	Jenny	Jenny's Brother	Jenny's Mom	Jenny's Dad	one: Where did Jenny live before she moved?	New York	Utah	Austin	Seattle	multiple: What made Jenny happy about being in Utah?	the music	the pretty views	being with her mom	a little girl came to play	multiple: Why was Jenny sad about the move?	She had to leave her stuff	She didn't want to leave her soccer team	She had to leave her friends and her school	She didn't want to leave her family
17 | mc160.dev.16	Author: 4251880037;Work Time(s): 2649	Mike and Jeff are close friends. Their school is having a guessing game to guess how many\newlinegumballs are in a box. If they get the right amount they win $100. If they get close they\newlineget a $20 gift card. The box looks like it is missing some gumballs. It turns out some\newlinepeople are eating them when they place their guess. 100 people guessed and took a piece of\newlinecandy. The box is 10" by 10" by 10". Each gumball is 1" each. Mike guessed 500. Jeff\newlineguessed 800. They both said they would split their money they win, if they win.	multiple: Who is closer?	Both	Jeff	Mike	Neither	one: How likely would it be for one of them to win?	5/100	10/100	1/100	100/100	multiple: How likely would it be neither of them to win?	89/99	99/99	99/100	98/100	multiple: What is the right amount?	1000	800	900	700
18 | mc160.dev.17	Author: 1883940740;Work Time(s): 1321	Hannah and her friend Mary were bored.  They sat around the house and tried to think about\newlinewhat to do.  They petted the cat.  They drew pictures in Hannah's notebook.  They snuck\newlineinto Hannah's mother's closet to try on her shoes, but Hannah's mother caught them.  She\newlinesaid, "You girls need something to do.  Let's take a walk to the park!" Hannah and Mary\newlinelooked at each other, and then jumped up and down happily.  "The park sounds great!" said\newlineHannah.  "Let's go!" cried Mary.  So Hannah's mother packed up a snack of apples and\newlinecookies, and they all set off to walk to the park.  They walked down the sidewalk, looking\newlineat all the interesting things along the way.  Mary spotted a squirrel.  Hannah saw a\newlineyellow bird.  Hannah's mother pointed out the pretty yellow flowers growing in front of\newlineMr. Smith's house.  When they got to the park, Hannah's mother spread out a picnic blanket\newlineand the snack.  Hannah and Mary ran around chasing butterflies for a little time, and then\newlinesat down to eat their snacks.  When they finished, Hannah's mother put the leftovers in a\newlinetrash can.  As they walked back home, Hannah thought that the boring day had turned out\newlinequite well.	one: What did Hannah and Mary chase at the park?	butterflies	turtles	birds	ducks	one: What did Hannah's mother do with the leftovers?	threw it on the ground	there was no trash	Put it in the trash can	took it home	multiple: What did Hannah and Mary see on their way to the park?	A butterfly and a bird	A squirrel, a yellow bird, and pink flowers	A horse	A pink squirrel, a bird, and yellow flowers	multiple: What did Hannah and Mary do when they were bored?	sang songs and drew pictures	played games	Petted the cat and drew pictures	jumped rope
19 | mc160.dev.18	Author: 2195212743;Work Time(s): 5807	Douglas loves to play soccer. He plays for the Dolphins. He is very good.  He was excited\newlineabout the big game with the Lions.  The night before the game, he went to bed late.  He\newlinewas watching three TV shows that night.  First, was Muffins the Cat.  The second show was\newlineErnie the Talking Donkey.  The third was Laughing with Herman Hamster.  His Mom told him\newlineto go to bed, but Douglas didn't listen.  He fell asleep on the couch. He dreamed all\newlinenight.  First about sheep jumping fences.  Second about playing fetch the ball with\newlineRuffles. Third about Ernie the talking Donkey kicking a soccer ball over the moon. Fourth\newlineabout his favorite soccer player, Pele, head the ball in the goal.\newline\newlineFinally, the next morning, Douglas got up late because he was so tired.  His Mom called\newlinehim and the alarm went off, but he did not hear. To get Douglas up, his Mom got Ruffles\newlinethe dog to lick him in the face.  Douglas got up but had to eat breakfast fast.  Then he\newlinequickly dressed into his uniform.  He was yawning.\newline\newlineHis Mom drove him to the soccer field.  The game had started.  Douglas had to sit out the\newlinefirst quarter.  His team was losing one to nothing when Howard scored for the Lions.\newlineDouglas started the second quarter.  He was tired and could not keep up with the rest of\newlinehis team.  The coach was surprised that Douglas was so slow.  Usually he was fast.  After\newlinethe second quarter, the Dolphins were losing two to one after Howard scored again for the\newlineLions and Toby scored a goal for the Dolphins. While the coach gave energy drinks to the\newlineteam, Douglas fell asleep.  The third quarter started.\newline\newlineDouglas was snoring when the coach told him to go in.  When he saw Douglas was sleeping,\newlinehe sent Billy into the game.  Billy scored one goal and the Dolphins had tied the game two\newlineto two.  Ruffles the dog started barking and then licking Douglas in the face.  Douglas\newlinegot up and stretched.  He was finally well rested.  The coach saw Douglas and sent him\newlineinto the game.  Douglas remembered his dream.  In the last second, he headed the ball in\newlinethe goal like Pele. He won the game. The team cheered.\newline\newlineSince that time, Douglas goes to bed on time.  He always wants to be well rested.  His Mom\newlinewas right.  He gave her a hug.	multiple: What dream helped Douglas win the game?	He dreamed about Ernie the donkey kick the ball over the moon.	He dreamed about Pele heading the ball in the goal.	He dreamed about Ruffles fetching the ball.	He dreamed about sheep jumping over fences.	one: Who woke Douglas up by licking him in the face?	Muffin the cat.	Herman the hamster.	Ernie the donkey.	Ruffles the dog.	multiple: How many points did the Dolphins score and who scored the goals?	They scored two points.  Ruffles and Billy scored.	They scored three points.  Toby, Billy and Douglas scored.	They scored five points. Howard, Billy, Ruffles, Douglas, and Billy scored.	They scored one point.  Toby scored.	one: What game does Douglas love to play?	Douglas loves to play baseball.	Douglas loves to play soccer.	Douglas loves to play basketball.	Douglas loves to play cards.
20 | mc160.dev.19	Author: 259176131;Work Time(s): 1010	I'm here to tell you the story of a robot named Carl. He came from a far away land known as\newlineFactory. Carl was sad because he was missing a part called a tire. He also needed a sun\newlinegatherer. But, the tire was more important. Once Carl got all these parts he could travel\newlineto his new home in the nation of Lab and the city of Office. It was a tricky thing to get\newlinethere with missing parts. Just as he had given up hope Carl got a message from Mr. X\newlinesaying the new parts were ready to be delivered. This made the robot very happy. The parts\newlinearrived a few days later and Carl put them in with 2 days of work. After this Carl began\newlineto travel the last bit of his goal to get to his new job. After this Carl took 10 days to\newlineget to Lab.	one: What nation did Carl want to get to?	Carl	Office	Factory	Lab	multiple: Besides a tire what part did Carl need?	missing	important	tire	sun gatherer	multiple: Where did Carl come from?	Lab	Mr. X	Office	Factory	one: What was the only city in the story?	Office	Mr. X	Lab	Factory
21 | mc160.dev.20	Author: 1091830255;Work Time(s): 1853	On a hot summer day, Brian was walking home from the park. While walking, Brian passed his\newlinefavorite toy store, and saw that they had a new baseball glove in the window.  Brian's\newlinebaseball glove was very old and was ripped in a few places.  Brian really wanted the new\newlineglove because he wanted to show off his glove to his friends tomorrow. The cost of the\newlinenew glove was fifteen dollars, but when Brian checked his pockets for money, he only had\newlinesix dollars and fifty cents.  Brian ran home and went to look around his house for money.\newlineHe checked under his bed and found fifty cents under some toys.  He then checked all of\newlinehis pockets of his pants and shorts, and found another two dollars.  Brian then went to\newlinelook between the cushions on all of the couches in his house, and he found another three\newlinedollars.  After finally looking around his whole house, Brian knew that he still did not\newlinehave enough money to buy the new glove.  Brian went outside and saw his dad doing yard\newlinework. He told his dad that he would finish all the yard work for him, if he could have the\newlinemoney he needed for the new glove.  His dad said yes, so Brian spent the rest of the\newlineafternoon raking the yard, and bagging leaves.  Brian's dad was very proud that his son\newlinewas working hard for money. When Brian was finally done, Brian knew that he was too\newlinelate, and the toy store was closed.  Just as Brian was walking inside, he saw his dad walk\newlineup to home holding the new glove that he wanted.  Brian was so happy, and he and his dad\newlinespent the rest of the afternoon having a catch.	one: Why did Brian dad buy him the glove?	His dad wanted to him to practice.	His dad didn't want him to use his old glove.	His dad was proud that he was working hard.	His dad knew that he really wanted it in order to show off his friends.	one: How much money did Brian find under his bed?	Fifteen dollars	Two Dollars	Fifty cents	Three dollars	multiple: Why did Brian want a new glove?	So he could show it off to his friends.	He did not have any baseball glove.	He lost his old baseball glove.	So he could have a catch with his dad.	multiple: How much money did Brian have in total after looking in his house?	Fifteen dollars	Twelve dollars	Six dollars	Fifty dollars
22 | mc160.dev.21	Author: 1815495932;Work Time(s): 1548	On a nice and sunny day, Bob and Sally walked to the beach. When they got there, the first\newlinething they wanted to do was to look for buried treasure. To find the treasure they had\newlinebrought two shovels and two buckets. They both started digging holes in the sand with\newlinetheir shovels. After looking very hard for treasure for an hour, they didn't find\newlineanything. This made Bob and Sally very sad. They gave up and went to play in the\newlinewater. While they were playing in the water, Sally found a bottle with a little paper\newlineinside. Sally opened the bottle and found a treasure map. Sally showed the map to Bob and\newlinethey started to look for the treasure.  After walking every step that the map said, they\newlinestarted digging with their shovels. After digging a really a big hole, they found a\newlinebox. They were very happy that they found it and wanted to see what was inside. Bob slowly\newlineopened the box and there was a very big pearl.  Next, they ran to a special store to ask\newlineabout the pearl. The worker in the store told Bob and Sally that the pearl could make them\newlinerich. Bob and Sally looked at each other and decided not to sell it. They took the pearl\newlinehome and saved it in a special box, so they could remember their day at the beach.	one: What did Bob and Sally find in the box?	A coin	A pearl	A ring	A necklace	one: What did Sally find in the water?	A shell	A bucket	A bottle	A shovel	multiple: What did Bob and Sally do after they showed the pearl to the worker?	They sold it.	They left it at the beach.	They took it home.	They gave it away.	multiple: Why did Bob and Sally stop looking for the treasure?	They were sad at not finding anything.	They forgot to bring a shovel.	They did not want to find the treasure.	They got hungry.
23 | mc160.dev.22	Author: 3310356749;Work Time(s): 2220	It was a beautiful sunny and warm day. I was working outside in my garden. I was pulling\newlineweeds which is not my favorite job, but I was enjoying the day. I live by a lake so\newlinesometimes I take a break from my chores and look at the lake. It is so beautiful and it\newlinemakes me happy to look at the beautiful lake and see what animals I can find swimming in\newlineor near the lake.\newline\newlineOn this day, I kept hearing a low soft sound coming from the lake. I got up from my garden\newlineand walked to the lake. I kept hearing this strange sound. It sounded like someone talking\newlinein a very low voice. I thought it might be a lake bird because we see and hear them all of\newlinethe time. The lake birds have several different calls that tell what they want to "say" to\newlineother lake birds. There is the call when they are flying which is very hurried and\newlineshort. Then there is the "where are you" call which is long, slow and loud. But this sound\newlinewas not like any I had ever heard. I went to get the binoculars to see if I could spot\newlineanything. But, no luck. I still kept hearing this low talking sound. I had now totally\newlinegiven up weeding. Finding this strange sound was going to be more fun. But where was it\newlinecoming from? I looked again up and down the lake and saw nothing. Finally I went around to\newlinethe other side of the place where we keep our boats. There is an area there where it is\newlinenot a very deep part of the water. I spotted them! It was a mother lake bird and a father\newlinelake bird with a baby in between them. They were teaching the baby how to swim and eat\newlinefish. The low talking sound that I heard must have been them trying to teach the baby to\newlineswim and eat the fish. I sat there on the bank and watched for a half an hour. I felt very\newlinespecial that I got to see this. It was such a fun thing to see and way more fun than\newlinegardening.	one: What was I doing on this day at the beginning of the story?	fishing	sleeping	working in the garden	cooking	one: What did I finally see?	two lake birds	four lake birds	three lake birds	one lake bird	multiple: What was the sound that I kept hearing?	something that sounded like laughing	something that sounded like low talking	something that sounded like crying	something that sounded like singing	multiple: How did I feel at the end of the story?	happy	sick	sad	glum
24 | mc160.dev.23	Author: 3048636168;Work Time(s): 1252	One day Magneson took a walk in the park.  He passed some trees and a pond.  In the pond\newlinewas a duck named George.  George's wife was also in the pond.  Her name was Nancy.\newline\newlineMagneson walked over to the tree.  Nancy flew up into the tree.  She wanted to warn\newlineMagneson about the killer squirrel who lived inside of the tree.  A few years before, the\newlinesquirrel had thrown a chestnut at George and Nancy's son.  He was knocked out, and the\newlinesquirrel took him away.  He was never seen again.\newline\newlineMagneson asked what their son's name was.  They said it was Leonard.  But Magneson was\newlineonly making small talk.  He didn't believe the story about the killer squirrel.  Even if\newlinethere was one, there were many rocks by the pond that he could throw at the squirrel.  He\newlinecould also hide in the tall grass.\newline\newlineGeorge and Nancy were sorry to see that Magneson wouldn't listen.  They flew away, singing\newlinea sad song.  A short time later, the squirrel came out of the tree and threw a giant\newlinewalnut at Magneson.  No one ever saw Magneson again.	multiple: What was George's wife's name?	Magneson	George	Nancy	Leonard	multiple: Who did the squirrel throw things at?	Nellie and George	Leonard and Magneson	George and Leonard	Magneson and Nellie	one: What did the squirrel throw at Magneson?	a chestnut	a giant walnut	a duck	a rock	one: Where did Magneson walk?	in the trees	in the pond	in the park	in the tall grass
25 | mc160.dev.24	Author: 2612134556;Work Time(s): 2652	Every Monday morning, the little bad boy named Josh goes to school.\newline\newlineSuddenly, little Josh slips on a banana skin ...\newline\newline- Ouch, says Josh, I fell on this and in addition I got a bump on the forehead!\newline\newline- Wonderful! said the banana peel. I am Mary. I turned into banana skin after throwing trash on the school yard. You have saved me and now I'm back to good old Mary. What's your name?\newline\newline- Mine is Josh... I'm a late to class ... are you serious, where is the banana peel anyways?\newline\newline- The Banana, my dear Josh, was eaten by me, I threw the banana peel and turned into one ... now you saved me, can you see the banana peel you slipped on around here?\newline\newline- No, you are right.\newline\newline- Mary said:  Josh, Thank you\newline\newline- Excuse me, Mary ... I have to go ... Otherwise I'll be late for school ... And I would not want to upset the teacher.	one: Who slipped on a banana skin?	Josh	John	Mary	Kate	multiple: Why Josh was in such a hurry?	Josh had a soccer game to play.	Josh was going back home.	Josh was heading to the school yard.	Josh was late to class.	one: Who turned into banana skin after throwing trash on the school yard?	Mary	Kate	Josh	Peter	multiple: Who are the principal characters of the story	Mary and Kate	Mary and Josh	Josh and Peter	Kate and Josh
26 | mc160.dev.25	Author: 868073141;Work Time(s): 5062	Once there was a young boy named Bret who had a cat named Wolfgang.  The boy had really\newlinewanted a wolf for a pet, but his mother said wolves liked to hog the bathroom and liked\newlineto blow things down and they snored.  So the boy had to call his cat Wolfie.\newline\newlineHe had also thought about naming his cat Sir Purrsalot.  Bret himself planned to become a\newlineknight when he grew up (or maybe a cowboy) and thought Sir Purrsalot sounded like a good\newlinename for his brother knight.  The difficulty there was that Wolfie didn't purr a lot.  He\newlinepurred when he was being fed or petted, but no one could say he purred a lot.  Plus Bret's\newlinemother said knights liked to poke things with their swords and they also liked to hog the\newlinebathroom and they clanked.\newline\newlineSo Bret was left with a cat named Wolfgang.  The neighbors gave him strange looks when he\newlinestood in the front yard in the evening and yelled "Wolfie!  Here Wolfie!!!", to get\newlineWolfgang to come in for the night.  But Bret didn't care what anyone else thought.  He had\newlinea Wolfie and maybe he'd end up becoming a pet doctor when he grew up instead.	multiple: When did Wolfie purr?	when hogging the bathroom	when petted	when poked	when sleeping	multiple: What was the name of the cat?	Bret	Buster	Wolfgang	Sir Purrsalot	one: What was one reasong his mother didn't like knights?	they grew up	they purred	they snored	they clanked	one: What was one reason his mother didn't like wolves?	they yelled	they barked	they purred	they snored
27 | mc160.dev.26	Author: 472016790;Work Time(s): 2027	Sally liked going outside.  She put on her shoes. She went outside to walk.  She walked on\newlinethe green grass.  The sun was warm.  The trees were tall. The birds sang in the trees.\newlineSally liked how the birds can sing.  Sally likes to sing with the birds, outside.  Ring,\newlinering, is how the birds sang. Sally sang ring, ring, with the birds in the trees. Sally\newlinetook off her shoes.  Sally liked how the green grass was on her toes.  Sally's toes liked\newlinethe green grass.  Sally walked on the green grass some more.  She saw Missy the cat.\newlineMissy the cat meowed to Sally.  Sally waved to Missy the cat.  Sally likes Missy the cat.\newlineSally likes to meow to Missy the cat.  Meow, meow, Sally says to Missy the cat. Missy the\newlinecat walks away from Sally.  Sally hears her name.  Sally, Sally, come home, Sally's Mom\newlinecalls out.  Sally runs home to her Mom.  Sally liked going outside.	multiple: Why did Sally put on her shoes?	To wave to Missy the cat	To hear her name	Because she wanted to go outside	To come home	one: What did Sally like to do?	Sally liked going outside	walk on the green grass	put on her shoes	take off her shoes	one: What was the name of the cat?	Meow	Missy	Sally	Ring	multiple: Who called Sally?	Missy the cat	The birds	The trees	Her Mom
28 | mc160.dev.27	Author: 1429298732;Work Time(s): 2461	Tammy likes the park. There are swings at the park. There is a slide at the park.  \newline\newlineMary goes to the park with Tammy. They jump rope. They play tag. They like the park.\newline\newlineTammy and Mary have fun at the park. Tammy has a dog named Max. Tammy and Mary take Max to the park.\newline\newlineMax likes the park. He chases rabbits. He chases a ball. Tammy throws the ball to Max. Mary throws the ball to Max.\newline\newlineThe park is no fun in the rain. Tammy and Mary cannot go to the park when it rains. Mother\newlinesays no. They are sad when they cannot go to the park.\newline\newlineTammy and Mary play in the house when it rains. They play with dolls. They dress up and\newlinehave a tea party.\newline\newlineToday is sunny. Tammy and Mary can go to the park. Mother says yes. They can take Max to\newlinethe park. They are happy when it is sunny.	one: Who has a dog?	The park	Max	Tammy	Mary	multiple: What do Tammy and Mary do when it rains?	go to the park	Play with dolls, have a tea party	play ball	chase rabbits	multiple: Who likes to go to the park?	Dolls	Mother	Tammy and Mary	The rabbits	one: What is the the name of the dog?	Mother	Max	Tammy	Mary
29 | mc160.dev.28	Author: 2345117472;Work Time(s): 932	Once upon a time, there was a dog named Puddles. Puddles was lonely because he lived in an\newlinearea where there were no other dogs, but only cats. Day after day, Puddles would have to\newlineeat cat food and do cat things in order to fit in with the rest of his group. He found it\newlinevery boring and Puddles was sad. Puddles didn't even look like a cat!\newline\newlineAll of the other cats teased Puddles. "You're too big," they said. "You've got too long of\newlinea nose!" "Why are you panting like that?" Puddles knew that he was different.\newline\newlineOne day, Puddles chose to run away from all of the cats. The cats laughed at him. What a\newlinestupid dog! Didn't he know that there were monsters in the woods that could eat him?\newlinePuddles didn't care, because Puddles was sad enough to try.\newline\newlineSo Puddles packed up his things - his squeaky ball, his water dish, and his bone - and\newlineheaded off into the woods. He was finally happy! All of a sudden, Puddles turned. He\newlinesmelled a funny smell. It smelled like something he had never smelled before. He turned\newlinearound, and what did he see but another dog!\newline\newlinePuddles was so happy, he barked with joy. He went home with the other dog, who was named\newlineMittens, and to his family. Puddles was never lonely again.	multiple: Why did the cats not like him?	He didn't eat cat food	He had a long nose	He was different	He panted	one: Where did Puddles live in the beginning?	with cats and dogs	In a group of cats	In a group of dogs	With humans	multiple: What does Puddles choose to do?	Go into the woods	Go to sleep	Eat cat food	Become a cat	one: Who did Puddles find?	Food	A monster	A dog family	A group of cats
30 | mc160.dev.29	Author: 400332158;Work Time(s): 839	Once upon a time there was a princess who lived in a high tower and she was not allowed to\newlineleave because of her mean mother. One day she chose to leave but her mother would not let\newlineher. The princess climbed out the window of the high tower and climbed down the south wall\newlinewhen her mother was sleeping. She wandered out a good ways. Finally she went into the\newlineforest where there are no electric poles but where there are some caves.  There she met a\newlineyoung man who was running. His name was John. John asked the princess why such a beautiful\newlinewoman like her was out in the middle of a forest. She said that she had been trapped for\newlineher whole life by an evil woman who said she was her mother. The man said that he would\newlinetake the princess to a castle that was near. He also said that he thought that she may be\newlinethe missing princess. As they go through the forest they run into many problems. They see\newlinethat they are lost and have no way of finding where to go. After several days pass, the\newlineprincess climbs up to the top of a tree in order to find out where they are. She sees that\newlinethe castle where they want to go is not that far away and near a mountain. After thinking\newlineof the best way to get there, John and the princess go to the castle where they live for\newlinethe rest of their lives.	multiple: Where did the princess wander to after escaping?	Mountain	Forest	Cave	Castle	one: Who escaped from the tower?	Mother	Princess	Man	John	multiple: What did the princess climb to see the castle?	Electric pole	mountain	Tree	Castle	one: Where does the princess live in the beginning?	Castle	house	Cave	High Tower
31 | 


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   1 | ***************************************************
   2 | Story:            mc160.dev.0
   3 | Author:           2670363255
   4 | Work Time(s):     1446
   5 | 
   6 | It was Jessie Bear's birthday. She was having a party.  She asked her two best friends to
   7 | come to the party.  She made a big cake, and hung up some balloons.
   8 | 
   9 | Soon her friend Lion came over. Then her friend Tiger came over. Lion and Tiger brought
  10 | presents with them.
  11 | 
  12 | Jessie hugged her friends. She asked them if they would like to have cake. 
  13 | 
  14 | Yes! said Lion. Yes yes! said Tiger. Jessie cut the cake, and they all ate it together.
  15 | Then Jessie opened her presents. She got a new jump rope and a fun game.  She asked Lion
  16 | and Tiger to play the game with her.
  17 | 
  18 | The friends played and played. They all had a good time. Soon it was time for the party to
  19 | be over.
  20 | 
  21 | Lion and Tiger hugged Jessie and said goodbye to her.  Thanks for a great birthday! Jessie
  22 | Bear told her two best friends.
  23 | 
  24 | 1: one: Who was having a birthday?
  25 | *A) Jessie Bear
  26 |  B) no one
  27 |  C) Lion
  28 |  D) Tiger
  29 | 
  30 | 2: multiple: Who didn't come to the party?
  31 |  A) Lion
  32 |  B) Tiger
  33 | *C) Snake
  34 |  D) Jessie Bear
  35 | 
  36 | 3: multiple: How did Jessie get ready for the party?
  37 |  A) made cake and juice.
  38 | *B) made cake and hung balloons.
  39 |  C) made juice and cookies.
  40 |  D) made juice and hung balloons.
  41 | 
  42 | 4: one: How many friends came to Jessie's party?
  43 |  A) one
  44 | *B) two
  45 |  C) six
  46 |  D) four
  47 | 
  48 | 
  49 | ***************************************************
  50 | Story:            mc160.dev.1
  51 | Author:           3466834307
  52 | Work Time(s):     879
  53 | 
  54 | Sally had a very exciting summer vacation. She went to summer camp for the first time. She
  55 | made friends with a girl named Tina. They shared a bunk bed in their cabin. Sally's
  56 | favorite activity was walking in the woods because she enjoyed nature. Tina liked arts and
  57 | crafts. Together, they made some art using leaves they found in the woods. Even after she
  58 | fell in the water, Sally still enjoyed canoeing. She was sad when the camp was over, but
  59 | promised to keep in touch with her new friend.
  60 | 
  61 | Sally went to the beach with her family in the summer as well. She loves the beach. Sally
  62 | collected shells and mailed some to her friend, Tina, so she could make some arts and
  63 | crafts with them. Sally liked fishing with her brothers, cooking on the grill with her dad,
  64 | and swimming in the ocean with her mother.
  65 | 
  66 | The summer was fun, but Sally was very excited to go back to school. She missed her
  67 | friends and teachers. She was excited to tell them about her summer vacation.
  68 | 
  69 | 1: multiple: Who went to the beach with Sally?
  70 |  A) her sisters
  71 |  B) Tina
  72 | *C) her brothers, mother, and father
  73 |  D) herself
  74 | 
  75 | 2: multiple: What did Sally promise to do?
  76 |  A) Learn to ride a bike.
  77 |  B) Go to a baseball game.
  78 |  C) Go back to the beach.
  79 | *D) Keep in touch with her new friend, Tina.
  80 | 
  81 | 3: one: Why does Sally like walking in the woods?
  82 |  A) She likes to climb trees.
  83 |  B) She likes to play hide and go seek.
  84 |  C) She likes to swim.
  85 | *D) She likes nature.
  86 | 
  87 | 4: multiple: What did Sally do this summer?
  88 | *A) She went to summer camp and the beach.
  89 |  B) She went to Paris.
  90 |  C) She went to a baseball game.
  91 |  D) She went to summer school.
  92 | 
  93 | 
  94 | ***************************************************
  95 | Story:            mc160.dev.2
  96 | Author:           519010308
  97 | Work Time(s):     1458
  98 | 
  99 | Todd lived in a town outside the city . Unlike the city the town was peaceful and quiet
 100 | and full of trees, flowers and animals.  One day his dad came in from work and said "Come
 101 | on, son, I'm going to take you to the city." Todd was very exited so he put on his shoes
 102 | and ran to the car.  When they got to the city Todd was very surprised there were so many
 103 | cars and people, everyone seemed to be in a hurry. There were no trees, no flowers, and no
 104 | animals. Todd was so happy to get back home.  When his mom asked him about his trip to the
 105 | city Todd said,"There's no place like home."
 106 | 
 107 | 1: multiple: Where did Todd visit?
 108 | *A) The city
 109 |  B) His mom
 110 |  C) The town
 111 |  D) The animals
 112 | 
 113 | 2: multiple: What did Todd say when he got home from the city?
 114 |  A) There were so many trees and flowers.
 115 |  B) There were so many people in cars.
 116 | *C) There's no place like home.
 117 |  D) There were so many animals.
 118 | 
 119 | 3: one: Where does Todd live?
 120 |  A) The city
 121 |  B) with his mom
 122 |  C) with his dad
 123 | *D) In a town.
 124 | 
 125 | 4: multiple: What did Todd see when he got to the city?
 126 |  A) lots of animals
 127 |  B) his mom
 128 |  C) lots of trees and flowers
 129 | *D) lots of people and cars
 130 | 
 131 | 
 132 | ***************************************************
 133 | Story:            mc160.dev.3
 134 | Author:           1077562726
 135 | Work Time(s):     4133
 136 | 
 137 | Greta ran to the corner with her older brother Tony.  He had money for the ice cream truck
 138 | in his pocket and she was very happy. The ice cream truck had been parked at the curb
 139 | waiting for children for a very long time.  The ice cream truck driver thought that no
 140 | more children were coming to get ice cream so he started pulling away from the curb when
 141 | they got to the corner. They yelled.  They screamed, "Stop! Stop!" and jumped up and down
 142 | on the side walk trying to get him to see them. The driver of the truck saw them, waved at
 143 | them and smiled, pulled back to the curb and opened his truck up so that they could see
 144 | everything that he had for sale.  They were so excited. They saw some new treats. Tony
 145 | wanted to try something new. He got an ice cream sundae with chocolate ice cream and
 146 | nuts. He almost got a snow cone. Greta looked at everything that the ice cream truck
 147 | had. She saw candy, ice cream cones, snow cones, and everything else. It all looked so
 148 | good. But after looking at everything, she wanted to get an ice cream sandwich. She got
 149 | the ice cream sandwich. She bit into it and smiled. It tasted so good. She felt so
 150 | happy. Her brother, Tony, was happy too. He bit into his ice cream cone sundae and
 151 | grinned.  They walked home with their ice cream and told their mom about how close they
 152 | came to not getting their ice cream at all. Their mom was happy that the truck had stopped
 153 | for them. She said that they were very lucky to have gotten to the curb before the ice
 154 | cream truck left.
 155 | 
 156 | 1: multiple: What did the driver of the ice cream truck do when Greta and Tony got to the corner?
 157 | *A) He started pulling away from the curb.
 158 |  B) He played the truck's jingle.
 159 |  C) He stayed parked at the curb.
 160 |  D) He almost got a snow cone.
 161 | 
 162 | 2: multiple: What did the children do when they saw the ice cream truck driver pull away from the curb?
 163 |  A) They ran out into the street after the iced cream truck.
 164 | *B) They screamed, "Stop! Stop!".
 165 |  C) They stood on the corner and cried.
 166 |  D) They ate ice cream.
 167 | 
 168 | 3: multiple: What did Tony and Greta get from the iced cream truck?
 169 |  A) Tony got a snow cone. Greta got an ice cream sundae.
 170 |  B) Tony got a snow cone. Greta got an iced cream cone with chocolate iced cream and nuts.
 171 | *C) Tony got an ice cream sundae with chocolate ice cream and nuts.
 172 |  D) Greta and Tony ice cream cones.
 173 | 
 174 | 4: multiple: What did Greta and Tony do after they got their ice cream?
 175 |  A) They walked to a friend's house and talked to his mother about what happened.
 176 | *B) They bit into it.
 177 |  C) They got in the truck.
 178 |  D) They walked home and went outside in their back yard to play.
 179 | 
 180 | 
 181 | ***************************************************
 182 | Story:            mc160.dev.4
 183 | Author:           2626224031
 184 | Work Time(s):     2199
 185 | 
 186 | My parents, Kelly and Kelley, said that it was that time of year to take a family
 187 | vacation.  We've been to big ride parks that have hotels with large pools.  This year my
 188 | parents wanted to do something different.  They wanted to take us all to Elk River Castle.
 189 | 
 190 | After lots of planning we hit the road for our trip.  My Brother Kelsey and I enjoyed the
 191 | long car ride there.
 192 |   
 193 | Once we arrive, the castle looked much bigger than we had imagined.  There was so much to
 194 | see and so much to do.  There was a swimming pool, movie theater and an elevator to take
 195 | us from floor to floor.  What a magical place!  I was so excited because we had the whole
 196 | place to our family!
 197 |   
 198 | We spent our vacation playing around the huge castle and finding small mysterious places.
 199 | There was even a tiny room in the back of one of the closets.  My brother, Kelsey, and I
 200 | played hide and go seek for hours, watched movies and swam until the sun went down.
 201 | 
 202 | It was sad when our vacation finally came to an end but we made some amazing memories.
 203 | We'll never forget our trip to Elk River Castle!
 204 | 
 205 | 1: one: What was my brother's name?
 206 |  A) Kelly
 207 | *B) Kelsey
 208 |  C) Caden
 209 |  D) Colby
 210 | 
 211 | 2: one: Where did we go?
 212 |  A) Hood River Castle
 213 | *B) Elk River Castle
 214 |  C) White Fish Castle
 215 |  D) White Salmon Castle
 216 | 
 217 | 3: multiple: What did the castle have?
 218 |  A) A ball room
 219 | *B) A movie theater
 220 |  C) A gym
 221 |  D) A hot tub
 222 | 
 223 | 4: multiple: What did we do at the castle?
 224 |  A) Played ball
 225 |  B) Fished
 226 | *C) Swam in the swimming pool
 227 |  D) Ran in the woods
 228 | 
 229 | 
 230 | ***************************************************
 231 | Story:            mc160.dev.5
 232 | Author:           3983187336
 233 | Work Time(s):     1622
 234 | 
 235 | Once upon a time there a little girl named Ana. Ana was a smart girl. Everyone in Ana's
 236 | school knew and liked her very much. She had a big dream of becoming spelling bee
 237 | winner. Ana studied very hard to be the best she could be at spelling. Ana's best friend
 238 | would help her study every day after school. By the time the spelling bee arrived Ana and
 239 | her best friend were sure she would win. There were ten students in the spelling bee. This
 240 | made Ana very nervous, but when she looked out and saw her dad cheering her on she knew
 241 | she could do it. The spelling bee had five rounds and Ana made it through them all. She
 242 | was now in the finals. During the final round James, the boy she was in the finals with, was
 243 | given a really hard word and he spelled it wrong. All Ana had to do was spell this last
 244 | word and she would be the winner. Ana stepped to the microphone, thought really hard and
 245 | spelled the word. She waited and finally her teacher said "That is correct". Ana had won
 246 | the spelling bee. Ana was so happy. She won a trophy. Ana also won a big yellow
 247 | ribbon. The whole school was also happy, and everyone clapped for her. The whole school
 248 | went outside. They had a picnic to celebrate Ana winning.
 249 | 
 250 | 1: multiple: What made Ana very nervous?
 251 | *A) The other ten students
 252 |  B) Her best friend
 253 |  C) The bright lights
 254 |  D) The big stage
 255 | 
 256 | 2: multiple: Where did the school have the picnic?
 257 |  A) The gym
 258 |  B) Ana's house
 259 | *C) Outside
 260 |  D) Ana's classroom
 261 | 
 262 | 3: one: What was Ana's big dream?
 263 |  A) Becoming a ballerina
 264 |  B) Becoming a famous singer
 265 |  C) Becoming class president
 266 | *D) Becoming spelling bee winner
 267 | 
 268 | 4: one: Who helped Ana study everyday?
 269 |  A) Her dad
 270 | *B) Her best friend
 271 |  C) Her mom
 272 |  D) Her sister
 273 | 
 274 | 
 275 | ***************************************************
 276 | Story:            mc160.dev.6
 277 | Author:           1006609625
 278 | Work Time(s):     2342
 279 | 
 280 | Roger was a grasshopper. He loved to hop. He hopped everywhere by himself. One day when he
 281 | was hopping around he bumped into a frog sitting on a log. The frog told him his name was
 282 | Gilbert. Gilbert told Roger that it had been a long time since he bumped into
 283 | anybody. Roger told him that since both grasshoppers and frogs like to jump they would
 284 | make great friends. The next day they were hopping through a field and they saw something
 285 | very strange.  In a pond they saw a spider floating on a lily pad. The spider was very sad
 286 | because he did not have any friends. Roger and Gilbert asked him why he didn't have any
 287 | friends. The spider told them that everybody would scream and run away when they saw him.
 288 | Roger and Gilbert told him that he didn't look scary to them and that he could come along
 289 | with them if he wanted. So Sam the spider said yes, and the three of them began a life
 290 | time friendship full of adventures.
 291 | 
 292 | 1: multiple: What did Roger like to do?
 293 |  A) Bump.
 294 | *B) Hop.
 295 |  C) Swim.
 296 |  D) Float.
 297 | 
 298 | 2: one: What was the spider sitting on in the pond?
 299 |  A) branch
 300 | *B) Lily pad
 301 |  C) land
 302 |  D) log
 303 | 
 304 | 3: multiple: What character is not in the story?
 305 |  A) spider
 306 | *B) lady bug
 307 |  C) grasshopper
 308 |  D) frog
 309 | 
 310 | 4: one: What was the spider's name?
 311 |  A) Roger
 312 |  B) Sarah
 313 |  C) Gilbert
 314 | *D) Sam
 315 | 
 316 | 
 317 | ***************************************************
 318 | Story:            mc160.dev.7
 319 | Author:           259176131
 320 | Work Time(s):     882
 321 | 
 322 | The cute red ball rolled over to the blue ball and said hello. The blue ball was scared
 323 | and went to cry to the green ball. The green ball laughed at the blue ball. Then the green
 324 | ball told the orange ball that blue ball was stupid. Most felt this was not good to do and
 325 | so they punished the green ball by taking away all his air.
 326 | 
 327 | From that day on everyone saw the air-less green ball and knew that they could not do or
 328 | say any bad things. This is how the trouble started. The purple ball used the fear of
 329 | everyone to become the leader that they all feared. The purple ball was mean to
 330 | everyone. Until one day the red ball spoke up and got all the other colored balls together
 331 | and they took the air from the purple ball and put it in the green ball. Sadly, the green
 332 | ball had been without air for too long and was dead.
 333 | 
 334 | 1: multiple: What color ball was the third brought up in the story?
 335 | *A) green
 336 |  B) blue
 337 |  C) red
 338 |  D) purple
 339 | 
 340 | 2: one: Which color ball became the leader?
 341 |  A) green
 342 |  B) blue
 343 |  C) red
 344 | *D) purple
 345 | 
 346 | 3: multiple: What color of ball scared the blue ball?
 347 |  A) purple
 348 | *B) red
 349 |  C) orange
 350 |  D) green
 351 | 
 352 | 4: one: At they end of the story, what was the state of the green ball.
 353 |  A) cute
 354 | *B) dead
 355 |  C) fear
 356 |  D) taking
 357 | 
 358 | 
 359 | ***************************************************
 360 | Story:            mc160.dev.8
 361 | Author:           863905974
 362 | Work Time(s):     329
 363 | 
 364 | Sara wanted to play on a baseball team. She had never tried to swing a bat and hit a
 365 | baseball before. Her Dad gave her a bat and together they went to the park to
 366 | practice. Sara wondered if she could hit a ball. She wasn't sure if she would be any
 367 | good. She really wanted to play on a team and wear a real uniform. She couldn't wait to
 368 | get to the park and test out her bat. When Sara and her Dad reached the park, Sara grabbed
 369 | the bat and stood a few steps away from her Dad. Sara waited as her Dad pitched the ball
 370 | to her. Her heart was beating fast. She missed the first few pitches. She felt like
 371 | quitting but kept trying. Soon she was hitting the ball very far. She was very happy and
 372 | she couldn't wait to sign up for a real team. Her Dad was very proud of her for not giving
 373 | up.
 374 | 
 375 | 1: multiple: Why was Sara practicing?
 376 |  A) She wanted to show off
 377 |  B) She didn't want to do her homework
 378 | *C) She wanted to play on a team
 379 |  D) She was bored
 380 | 
 381 | 2: one: Who pitched the ball to Sara?
 382 |  A) Her Mom
 383 |  B) Her Sister
 384 | *C) Her Dad
 385 |  D) Her Brother
 386 | 
 387 | 3: multiple: Why was Sara's Dad proud of her?
 388 |  A) She didn't get dirty
 389 |  B) She didn't break the bat
 390 | *C) She didn't quit
 391 |  D) She was better than her Dad
 392 | 
 393 | 4: one: Where did Sara go to practice hitting the ball?
 394 |  A) A stadium
 395 |  B) Her yard
 396 | *C) The park
 397 |  D) Her bedroom
 398 | 
 399 | 
 400 | ***************************************************
 401 | Story:            mc160.dev.9
 402 | Author:           2311321761
 403 | Work Time(s):     634
 404 | 
 405 | Peter was a very sad puppy.  He had been inside of the pet store for a very long time.  In
 406 | fact, he had been there for three months!  Peter had seen many other puppies find a
 407 | person; he began to wonder why he could not get one.  He thought that maybe his fur was
 408 | not pretty enough or maybe his bark was not loud enough.  He tried and tried to please
 409 | every person who came to the store, but they all picked smaller puppies.  However, one day
 410 | all of this changed.  Sammie came into the store looking for a golden puppy.  She wanted a
 411 | puppy she could snuggle with.  It so happened that Peter was very sad and tired that day.
 412 | Sammie came to hold him.  Peter wanted to show off his bark, but he was too tired.  He
 413 | fell right to sleep.  Sammie loved him at once and loved holding him in her arms.  Sammie
 414 | took Peter home that day, and they made lots of fun memories.
 415 | 
 416 | 1: multiple: What did Peter want to do when Sammie came?
 417 |  A) He wanted to show off his fur
 418 |  B) He wanted to be beautiful
 419 |  C) He wanted to snuggle with her
 420 | *D) He wanted to show off his bark
 421 | 
 422 | 2: one: Where was Peter?
 423 |  A) Sad and tired
 424 | *B) At the pet store
 425 |  C) Home
 426 |  D) At the park practicing his bark
 427 | 
 428 | 3: multiple: What did Peter actually do when Sammie came?
 429 |  A) Peter showed off his fur
 430 |  B) Peter showed off his bark
 431 | *C) Peter fell asleep
 432 |  D) Peter wondered if he would be a good enough puppy
 433 | 
 434 | 4: multiple: What kind of puppy did Sammie want?
 435 |  A) A golden puppy that was small
 436 |  B) A golden puppy with shiny fur
 437 |  C) A puppy with a loud bark she could snuggle with
 438 | *D) A golden puppy she could snuggle with
 439 | 
 440 | 
 441 | ***************************************************
 442 | Story:            mc160.dev.10
 443 | Author:           3842083771
 444 | Work Time(s):     4095
 445 | 
 446 | Luna the hawk wanted some socks. It was the middle of winter and sitting on tree branches
 447 | made her feet very cold. Luna hoped that her friends could help her find some socks. She
 448 | flew to the old maple tree where Olive the owl lived.
 449 | 
 450 | "Olive, may I please borrow a pair of your socks?" she asked.
 451 | 
 452 | Olive the owl looked surprised. "Luna, I have no use for socks because my legs and toes
 453 | have thick feathers. Go visit one of the animals that walk on four legs. They might have
 454 | extra socks you could borrow."
 455 | 
 456 | Luna flew across the field and landed next to the icy creek. Rose the raccoon was teaching
 457 | her six babies how to wash their paws. The water was very cold, but the babies were having
 458 | fun.
 459 | 
 460 | "Rose, my bare legs and bare toes are so cold, may I please borrow a pair of your socks?"
 461 | begged Luna.
 462 | 
 463 | Rose laughed hard. "Silly Luna, I do not have socks. Look at my legs and feet. They are
 464 | covered with thick, warm fur. I'm sorry I cannot help you. Go visit the humans. Sometimes
 465 | I tip over their garbage cans at night when I am looking for food. Once I saw a pair of
 466 | socks."
 467 | 
 468 | Luna was very afraid of humans. Her grandmother and mother had warned her about them. She
 469 | was told that some humans are mean and hurt hawks. Her feet were so cold that it was
 470 | difficult to grip tree branches. She became brave. She flew to the farmhouse on the big
 471 | hill. When she landed on the roof, she could not believe her eyes. She saw socks! In late
 472 | autumn, Henrietta the human had put laundry outside to dry and she had forgotten to bring
 473 | in one tiny pair of socks. The socks were hanging on the clothesline by two wooden
 474 | pins. Luna used her powerful beak to break the pins. She put on the socks and then flew
 475 | back to her home in the huge tree. When she landed, her feet were warm and dry. Luna was
 476 | very happy.
 477 | 
 478 | 1: one: Why did Olive the owl not have any socks?
 479 |  A) She had given her socks to another friend.
 480 |  B) All of her socks were in the dirty laundry.
 481 | *C) She has thick feathers on her legs and toes.
 482 |  D) She wore ski boots instead of socks.
 483 | 
 484 | 2: multiple: Why was Luna afraid of humans?
 485 | *A) Her grandmother and mother had told stories about mean humans hurting hawks.
 486 |  B) Humans were large and scary-looking.
 487 |  C) Humans put garbage in the hawks' nests.
 488 |  D) Humans stole all of the hawks' food.
 489 | 
 490 | 3: multiple: Which animal did Luna not visit?
 491 |  A) Olive the owl
 492 |  B) Rose the raccoon
 493 | *C) Opal the otter
 494 |  D) Henrietta the human
 495 | 
 496 | 4: multiple: How could the baby raccoons play in the icy creek without hurting their paws?
 497 |  A) Because their mother made sure they had warm mittens to keep their paws dry.
 498 |  B) Because their mother taught them how to play in the water without getting cold.
 499 |  C) Because their legs and feet are tough from tipping over garbage cans.
 500 | *D) Because their legs and feet have a thick covering of fur that keeps them warm.
 501 | 
 502 | 
 503 | ***************************************************
 504 | Story:            mc160.dev.11
 505 | Author:           534571148
 506 | Work Time(s):     3659
 507 | 
 508 | Once upon a time a young boy and young girl set out on a trip to the beach. They packed a
 509 | few towels, an umbrella, a few beach chairs and a lunch cooler. They drove to the crowded
 510 | beach parking lot and spent almost an hour trying to find a parking spot. Once they found
 511 | a spot they parked and began walking to the beach area. They found a nice spot with a good
 512 | view of the water and set up their belongings. Once they sat down they began to enjoy a
 513 | nice lunch on the beach. They watched the boats go by and people playing in the water. It
 514 | was a wonderful day and one they would always remember. Once they arrived home they
 515 | suddenly found out that they both had a pretty good sunburn. They both said that next time
 516 | they would use sun screen.
 517 | 
 518 | 1: multiple: Was it a good day for the couple, and what did they find out when they got home?
 519 | *A) It was a good day, and they found that they were sunburned
 520 |  B) It was not a good day, and they found they were sunburned.
 521 |  C) It was a good day, and they found they were late getting home
 522 |  D) It was not a good day, and they found that they got a parking ticket
 523 | 
 524 | 2: multiple: Where were the couple going and how did they get their?
 525 |  A) The beach and by Bike
 526 |  B) The park and by bike
 527 |  C) The store and by car
 528 | *D) The beach and by car
 529 | 
 530 | 3: one: Besides boats what did the couple watch?
 531 |  A) dolphins
 532 |  B) people making sand castles
 533 | *C) people playing in the water
 534 |  D) children playing in the sand
 535 | 
 536 | 4: one: It took the young couple how long to find a parking spot?
 537 |  A) almost a half hour
 538 |  B) only a short time
 539 | *C) almost an hour
 540 |  D) over an hour
 541 | 
 542 | 
 543 | ***************************************************
 544 | Story:            mc160.dev.12
 545 | Author:           212417544
 546 | Work Time(s):     998
 547 | 
 548 | Three little kids lived in a great big house with a great big cat and many places for a
 549 | great big cat to hide.  Their great big cat was named Cowboy.  And Cowboy was not a very
 550 | nice cat.  Cowboy liked to bite and chew and scratch a great many things.  When Cowboy was
 551 | happy, which was not very often, Cowboy liked to bite in to a blanket or soft toy and
 552 | carry it around in his mouth.  When Cowboy was hungry he liked to bite bright red tomatoes
 553 | and suck out all the juice and seeds.  And when Cowboy was feeling mean he liked to hide.
 554 | Cowboy would hide, curled up tight in a ball under a blanket or behind a corner and wait
 555 | for one of the little kids to pass by.  When they did pass by Cowboy would jump at their
 556 | feet and try to bite and scratch them.  He did not know that what he was doing was not
 557 | very nice.  Cowboy was only a cat.  A great big cat that did not know any better.
 558 | 
 559 | 1: one: What was the cat's name?
 560 |  A) Tony
 561 | *B) Cowboy
 562 |  C) Cat
 563 |  D) Chowder
 564 | 
 565 | 2: one: What did Cowboy like to eat when he was hungry?
 566 |  A) Cowboy liked to eat cat food.
 567 |  B) Cowboy liked to eat toys.
 568 |  C) Cowboy liked to eat blankets.
 569 | *D) Cowboy liked to eat tomatoes.
 570 | 
 571 | 3: multiple: When Cowboy felt mean he liked to...
 572 |  A) run and hide.
 573 |  B) chew on toys.
 574 |  C) bite the blankets.
 575 | *D) hide and jump.
 576 | 
 577 | 4: multiple: Cowboy was a...
 578 |  A) a tiny little cat.
 579 |  B) a normal size cat.
 580 | *C) great big cat.
 581 |  D) a great big dog.
 582 | 
 583 | 
 584 | ***************************************************
 585 | Story:            mc160.dev.13
 586 | Author:           1460358657
 587 | Work Time(s):     867
 588 | 
 589 | On the first day of school, Mrs. Law asked all the students to write a story telling her
 590 | what they did over the summer. She told the students that they were going to read them in
 591 | front of the class. This was going to help everyone get to know more about each other.
 592 | 
 593 | When all the students were done writing their stories, Anna raised her hand to read hers
 594 | first. Mrs. Law smiled at Anna's excitement to share her story with the class. She told
 595 | all the students to sit down and listen to Anna.
 596 | 
 597 | Anna started reading her story. All the other students quickly paid attention, as her
 598 | story was telling about her vacation to a park with lots of rides. Anna told them that she
 599 | rode a huge ride called, "Superman," which was her favorite. After Anna finished reading
 600 | her story, all the students clapped and said that they wished that they could hear
 601 | more. Anna told them to tell their mommies and daddies to take them to visit the rides
 602 | next summer.
 603 | 
 604 | 1: multiple: Why did the students have to read their stories to the class?
 605 |  A) to get to know who had the best summer
 606 |  B) to get to know Mrs. Law
 607 | *C) to help them get to know more about each other
 608 |  D) to get to know who had the best mommy and daddy
 609 | 
 610 | 2: one: What did the students have to write about?
 611 |  A) the first day of school
 612 |  B) Mrs. Law
 613 |  C) Anna's summer vacation
 614 | *D) what they did over the summer
 615 | 
 616 | 3: multiple: Why did Mrs. Law smile at Anna?
 617 |  A) because Anna told the class a joke
 618 | *B) because she raised her hand to read her story first
 619 |  C) because Anna laughed
 620 |  D) because Anna rode a huge ride
 621 | 
 622 | 4: one: What was the huge ride called that Anna told the class about?
 623 |  A) Batman
 624 | *B) Superman
 625 |  C) there wasn't one
 626 |  D) Jolly Green Giant
 627 | 
 628 | 
 629 | ***************************************************
 630 | Story:            mc160.dev.14
 631 | Author:           534571148
 632 | Work Time(s):     10766
 633 | 
 634 | This is a story about a bear and a wolf. The bear met the wolf one day in the woods. The
 635 | bear said to the wolf, would you like to go to the river with me? The wolf said yes, he
 636 | would like to go to the river. When the bear and the wolf got to the river they found that
 637 | a beaver had built a bridge to the other side of the river. The bear and the wolf crossed
 638 | the bridge that was built by the beaver and found that they were now in a part of the
 639 | woods they had never seen before. A little worried that they may get lost in this part of
 640 | the woods they had never seen before the bear and the wolf turned around. They went back
 641 | over the bridge and were happy to be back in a part of the woods they knew so well. The
 642 | beaver thanked both the bear and the wolf for trying out his new bridge and then started
 643 | to build yet another bridge close to the first bridge. He was a very busy beaver.
 644 | 
 645 | 1: one: Which animal built a bridge?
 646 | *A) the beaver
 647 |  B) the bear
 648 |  C) the dog
 649 |  D) the wolf
 650 | 
 651 | 2: multiple: what did the bear and wolf cross, and why did they turn back?
 652 |  A) a bridge, and they got hungry.
 653 |  B) a lake, and they did not want to get lost.
 654 |  C) a field and they did not want to get lost.
 655 | *D) a bridge, and they did not want to get lost.
 656 | 
 657 | 3: multiple: What did the beaver build and why did he thank the bear and wolf?
 658 |  A) a bridge, and for helping him to build the bridge.
 659 |  B) a house, and for trying out the bridge.
 660 | *C) a bridge, and for trying out the bridge.
 661 |  D) a bridge, and for bring him food
 662 | 
 663 | 4: one: This is a story of which two animals taking a walk in the woods?
 664 |  A) a bear and a beaver
 665 |  B) a dog and a wolf
 666 |  C) a bear and a dog
 667 | *D) a bear and a wolf
 668 | 
 669 | 
 670 | ***************************************************
 671 | Story:            mc160.dev.15
 672 | Author:           3960091198
 673 | Work Time(s):     725
 674 | 
 675 | Jenny's family lived in a small apartment in Seattle.  One day Jenny came home from school
 676 | and her mom told her that the family was moving to Utah.  Jenny was sad to leave her
 677 | friends. Jenny was sad to leave her school.  Jenny helped her mom pack boxes and clean
 678 | their apartment to get ready for the move.  Soon the day came when Jenny's dad brought a
 679 | large truck to the parking lot and all of the family's things were put inside.  Jenny and
 680 | her mom rode in their car and her dad drove the truck towards Utah.  Jenny loved getting
 681 | to eat lots of yummy fast food on the way.  When the family got to their new home in Utah,
 682 | Jenny helped her parents to take all of the boxes into the house.  She loved her new
 683 | bedroom!  When Jenny was emptying box of her toys, there was a knock at the door.  It was
 684 | a little girl who wanted Jenny to play! Jenny was going to like Utah!
 685 | 
 686 | 1: one: Who drove the truck?
 687 |  A) Jenny
 688 |  B) Jenny's Brother
 689 |  C) Jenny's Mom
 690 | *D) Jenny's Dad
 691 | 
 692 | 2: one: Where did Jenny live before she moved?
 693 |  A) New York
 694 |  B) Utah
 695 |  C) Austin
 696 | *D) Seattle
 697 | 
 698 | 3: multiple: What made Jenny happy about being in Utah?
 699 |  A) the music
 700 |  B) the pretty views
 701 |  C) being with her mom
 702 | *D) a little girl came to play
 703 | 
 704 | 4: multiple: Why was Jenny sad about the move?
 705 |  A) She had to leave her stuff
 706 |  B) She didn't want to leave her soccer team
 707 | *C) She had to leave her friends and her school
 708 |  D) She didn't want to leave her family
 709 | 
 710 | 
 711 | ***************************************************
 712 | Story:            mc160.dev.16
 713 | Author:           4251880037
 714 | Work Time(s):     2649
 715 | 
 716 | Mike and Jeff are close friends. Their school is having a guessing game to guess how many
 717 | gumballs are in a box. If they get the right amount they win $100. If they get close they
 718 | get a $20 gift card. The box looks like it is missing some gumballs. It turns out some
 719 | people are eating them when they place their guess. 100 people guessed and took a piece of
 720 | candy. The box is 10" by 10" by 10". Each gumball is 1" each. Mike guessed 500. Jeff
 721 | guessed 800. They both said they would split their money they win, if they win.
 722 | 
 723 | 1: multiple: Who is closer?
 724 |  A) Both
 725 | *B) Jeff
 726 |  C) Mike
 727 |  D) Neither
 728 | 
 729 | 2: one: How likely would it be for one of them to win?
 730 |  A) 5/100
 731 |  B) 10/100
 732 | *C) 1/100
 733 |  D) 100/100
 734 | 
 735 | 3: multiple: How likely would it be neither of them to win?
 736 |  A) 89/99
 737 |  B) 99/99
 738 |  C) 99/100
 739 | *D) 98/100
 740 | 
 741 | 4: multiple: What is the right amount?
 742 |  A) 1000
 743 |  B) 800
 744 | *C) 900
 745 |  D) 700
 746 | 
 747 | 
 748 | ***************************************************
 749 | Story:            mc160.dev.17
 750 | Author:           1883940740
 751 | Work Time(s):     1321
 752 | 
 753 | Hannah and her friend Mary were bored.  They sat around the house and tried to think about
 754 | what to do.  They petted the cat.  They drew pictures in Hannah's notebook.  They snuck
 755 | into Hannah's mother's closet to try on her shoes, but Hannah's mother caught them.  She
 756 | said, "You girls need something to do.  Let's take a walk to the park!" Hannah and Mary
 757 | looked at each other, and then jumped up and down happily.  "The park sounds great!" said
 758 | Hannah.  "Let's go!" cried Mary.  So Hannah's mother packed up a snack of apples and
 759 | cookies, and they all set off to walk to the park.  They walked down the sidewalk, looking
 760 | at all the interesting things along the way.  Mary spotted a squirrel.  Hannah saw a
 761 | yellow bird.  Hannah's mother pointed out the pretty yellow flowers growing in front of
 762 | Mr. Smith's house.  When they got to the park, Hannah's mother spread out a picnic blanket
 763 | and the snack.  Hannah and Mary ran around chasing butterflies for a little time, and then
 764 | sat down to eat their snacks.  When they finished, Hannah's mother put the leftovers in a
 765 | trash can.  As they walked back home, Hannah thought that the boring day had turned out
 766 | quite well.
 767 | 
 768 | 1: one: What did Hannah and Mary chase at the park?
 769 | *A) butterflies
 770 |  B) turtles
 771 |  C) birds
 772 |  D) ducks
 773 | 
 774 | 2: one: What did Hannah's mother do with the leftovers?
 775 |  A) threw it on the ground
 776 |  B) there was no trash
 777 | *C) Put it in the trash can
 778 |  D) took it home
 779 | 
 780 | 3: multiple: What did Hannah and Mary see on their way to the park?
 781 |  A) A butterfly and a bird
 782 | *B) A squirrel, a yellow bird, and pink flowers
 783 |  C) A horse
 784 |  D) A pink squirrel, a bird, and yellow flowers
 785 | 
 786 | 4: multiple: What did Hannah and Mary do when they were bored?
 787 |  A) sang songs and drew pictures
 788 |  B) played games
 789 | *C) Petted the cat and drew pictures
 790 |  D) jumped rope
 791 | 
 792 | 
 793 | ***************************************************
 794 | Story:            mc160.dev.18
 795 | Author:           2195212743
 796 | Work Time(s):     5807
 797 | 
 798 | Douglas loves to play soccer. He plays for the Dolphins. He is very good.  He was excited
 799 | about the big game with the Lions.  The night before the game, he went to bed late.  He
 800 | was watching three TV shows that night.  First, was Muffins the Cat.  The second show was
 801 | Ernie the Talking Donkey.  The third was Laughing with Herman Hamster.  His Mom told him
 802 | to go to bed, but Douglas didn't listen.  He fell asleep on the couch. He dreamed all
 803 | night.  First about sheep jumping fences.  Second about playing fetch the ball with
 804 | Ruffles. Third about Ernie the talking Donkey kicking a soccer ball over the moon. Fourth
 805 | about his favorite soccer player, Pele, head the ball in the goal.
 806 | 
 807 | Finally, the next morning, Douglas got up late because he was so tired.  His Mom called
 808 | him and the alarm went off, but he did not hear. To get Douglas up, his Mom got Ruffles
 809 | the dog to lick him in the face.  Douglas got up but had to eat breakfast fast.  Then he
 810 | quickly dressed into his uniform.  He was yawning.
 811 | 
 812 | His Mom drove him to the soccer field.  The game had started.  Douglas had to sit out the
 813 | first quarter.  His team was losing one to nothing when Howard scored for the Lions.
 814 | Douglas started the second quarter.  He was tired and could not keep up with the rest of
 815 | his team.  The coach was surprised that Douglas was so slow.  Usually he was fast.  After
 816 | the second quarter, the Dolphins were losing two to one after Howard scored again for the
 817 | Lions and Toby scored a goal for the Dolphins. While the coach gave energy drinks to the
 818 | team, Douglas fell asleep.  The third quarter started.
 819 | 
 820 | Douglas was snoring when the coach told him to go in.  When he saw Douglas was sleeping,
 821 | he sent Billy into the game.  Billy scored one goal and the Dolphins had tied the game two
 822 | to two.  Ruffles the dog started barking and then licking Douglas in the face.  Douglas
 823 | got up and stretched.  He was finally well rested.  The coach saw Douglas and sent him
 824 | into the game.  Douglas remembered his dream.  In the last second, he headed the ball in
 825 | the goal like Pele. He won the game. The team cheered.
 826 | 
 827 | Since that time, Douglas goes to bed on time.  He always wants to be well rested.  His Mom
 828 | was right.  He gave her a hug.
 829 | 
 830 | 1: multiple: What dream helped Douglas win the game?
 831 |  A) He dreamed about Ernie the donkey kick the ball over the moon.
 832 | *B) He dreamed about Pele heading the ball in the goal.
 833 |  C) He dreamed about Ruffles fetching the ball.
 834 |  D) He dreamed about sheep jumping over fences.
 835 | 
 836 | 2: one: Who woke Douglas up by licking him in the face?
 837 |  A) Muffin the cat.
 838 |  B) Herman the hamster.
 839 |  C) Ernie the donkey.
 840 | *D) Ruffles the dog.
 841 | 
 842 | 3: multiple: How many points did the Dolphins score and who scored the goals?
 843 |  A) They scored two points.  Ruffles and Billy scored.
 844 | *B) They scored three points.  Toby, Billy and Douglas scored.
 845 |  C) They scored five points. Howard, Billy, Ruffles, Douglas, and Billy scored.
 846 |  D) They scored one point.  Toby scored.
 847 | 
 848 | 4: one: What game does Douglas love to play?
 849 |  A) Douglas loves to play baseball.
 850 | *B) Douglas loves to play soccer.
 851 |  C) Douglas loves to play basketball.
 852 |  D) Douglas loves to play cards.
 853 | 
 854 | 
 855 | ***************************************************
 856 | Story:            mc160.dev.19
 857 | Author:           259176131
 858 | Work Time(s):     1010
 859 | 
 860 | I'm here to tell you the story of a robot named Carl. He came from a far away land known as
 861 | Factory. Carl was sad because he was missing a part called a tire. He also needed a sun
 862 | gatherer. But, the tire was more important. Once Carl got all these parts he could travel
 863 | to his new home in the nation of Lab and the city of Office. It was a tricky thing to get
 864 | there with missing parts. Just as he had given up hope Carl got a message from Mr. X
 865 | saying the new parts were ready to be delivered. This made the robot very happy. The parts
 866 | arrived a few days later and Carl put them in with 2 days of work. After this Carl began
 867 | to travel the last bit of his goal to get to his new job. After this Carl took 10 days to
 868 | get to Lab.
 869 | 
 870 | 1: one: What nation did Carl want to get to?
 871 |  A) Carl
 872 |  B) Office
 873 |  C) Factory
 874 | *D) Lab
 875 | 
 876 | 2: multiple: Besides a tire what part did Carl need?
 877 |  A) missing
 878 |  B) important
 879 |  C) tire
 880 | *D) sun gatherer
 881 | 
 882 | 3: multiple: Where did Carl come from?
 883 |  A) Lab
 884 |  B) Mr. X
 885 |  C) Office
 886 | *D) Factory
 887 | 
 888 | 4: one: What was the only city in the story?
 889 | *A) Office
 890 |  B) Mr. X
 891 |  C) Lab
 892 |  D) Factory
 893 | 
 894 | 
 895 | ***************************************************
 896 | Story:            mc160.dev.20
 897 | Author:           1091830255
 898 | Work Time(s):     1853
 899 | 
 900 | On a hot summer day, Brian was walking home from the park. While walking, Brian passed his
 901 | favorite toy store, and saw that they had a new baseball glove in the window.  Brian's
 902 | baseball glove was very old and was ripped in a few places.  Brian really wanted the new
 903 | glove because he wanted to show off his glove to his friends tomorrow. The cost of the
 904 | new glove was fifteen dollars, but when Brian checked his pockets for money, he only had
 905 | six dollars and fifty cents.  Brian ran home and went to look around his house for money.
 906 | He checked under his bed and found fifty cents under some toys.  He then checked all of
 907 | his pockets of his pants and shorts, and found another two dollars.  Brian then went to
 908 | look between the cushions on all of the couches in his house, and he found another three
 909 | dollars.  After finally looking around his whole house, Brian knew that he still did not
 910 | have enough money to buy the new glove.  Brian went outside and saw his dad doing yard
 911 | work. He told his dad that he would finish all the yard work for him, if he could have the
 912 | money he needed for the new glove.  His dad said yes, so Brian spent the rest of the
 913 | afternoon raking the yard, and bagging leaves.  Brian's dad was very proud that his son
 914 | was working hard for money. When Brian was finally done, Brian knew that he was too
 915 | late, and the toy store was closed.  Just as Brian was walking inside, he saw his dad walk
 916 | up to home holding the new glove that he wanted.  Brian was so happy, and he and his dad
 917 | spent the rest of the afternoon having a catch.
 918 | 
 919 | 1: one: Why did Brian dad buy him the glove?
 920 |  A) His dad wanted to him to practice.
 921 |  B) His dad didn't want him to use his old glove.
 922 | *C) His dad was proud that he was working hard.
 923 |  D) His dad knew that he really wanted it in order to show off his friends.
 924 | 
 925 | 2: one: How much money did Brian find under his bed?
 926 |  A) Fifteen dollars
 927 |  B) Two Dollars
 928 | *C) Fifty cents
 929 |  D) Three dollars
 930 | 
 931 | 3: multiple: Why did Brian want a new glove?
 932 | *A) So he could show it off to his friends.
 933 |  B) He did not have any baseball glove.
 934 |  C) He lost his old baseball glove.
 935 |  D) So he could have a catch with his dad.
 936 | 
 937 | 4: multiple: How much money did Brian have in total after looking in his house?
 938 |  A) Fifteen dollars
 939 | *B) Twelve dollars
 940 |  C) Six dollars
 941 |  D) Fifty dollars
 942 | 
 943 | 
 944 | ***************************************************
 945 | Story:            mc160.dev.21
 946 | Author:           1815495932
 947 | Work Time(s):     1548
 948 | 
 949 | On a nice and sunny day, Bob and Sally walked to the beach. When they got there, the first
 950 | thing they wanted to do was to look for buried treasure. To find the treasure they had
 951 | brought two shovels and two buckets. They both started digging holes in the sand with
 952 | their shovels. After looking very hard for treasure for an hour, they didn't find
 953 | anything. This made Bob and Sally very sad. They gave up and went to play in the
 954 | water. While they were playing in the water, Sally found a bottle with a little paper
 955 | inside. Sally opened the bottle and found a treasure map. Sally showed the map to Bob and
 956 | they started to look for the treasure.  After walking every step that the map said, they
 957 | started digging with their shovels. After digging a really a big hole, they found a
 958 | box. They were very happy that they found it and wanted to see what was inside. Bob slowly
 959 | opened the box and there was a very big pearl.  Next, they ran to a special store to ask
 960 | about the pearl. The worker in the store told Bob and Sally that the pearl could make them
 961 | rich. Bob and Sally looked at each other and decided not to sell it. They took the pearl
 962 | home and saved it in a special box, so they could remember their day at the beach.
 963 | 
 964 | 1: one: What did Bob and Sally find in the box?
 965 |  A) A coin
 966 | *B) A pearl
 967 |  C) A ring
 968 |  D) A necklace
 969 | 
 970 | 2: one: What did Sally find in the water?
 971 |  A) A shell
 972 |  B) A bucket
 973 | *C) A bottle
 974 |  D) A shovel
 975 | 
 976 | 3: multiple: What did Bob and Sally do after they showed the pearl to the worker?
 977 |  A) They sold it.
 978 |  B) They left it at the beach.
 979 | *C) They took it home.
 980 |  D) They gave it away.
 981 | 
 982 | 4: multiple: Why did Bob and Sally stop looking for the treasure?
 983 | *A) They were sad at not finding anything.
 984 |  B) They forgot to bring a shovel.
 985 |  C) They did not want to find the treasure.
 986 |  D) They got hungry.
 987 | 
 988 | 
 989 | ***************************************************
 990 | Story:            mc160.dev.22
 991 | Author:           3310356749
 992 | Work Time(s):     2220
 993 | 
 994 | It was a beautiful sunny and warm day. I was working outside in my garden. I was pulling
 995 | weeds which is not my favorite job, but I was enjoying the day. I live by a lake so
 996 | sometimes I take a break from my chores and look at the lake. It is so beautiful and it
 997 | makes me happy to look at the beautiful lake and see what animals I can find swimming in
 998 | or near the lake.
 999 | 
1000 | On this day, I kept hearing a low soft sound coming from the lake. I got up from my garden
1001 | and walked to the lake. I kept hearing this strange sound. It sounded like someone talking
1002 | in a very low voice. I thought it might be a lake bird because we see and hear them all of
1003 | the time. The lake birds have several different calls that tell what they want to "say" to
1004 | other lake birds. There is the call when they are flying which is very hurried and
1005 | short. Then there is the "where are you" call which is long, slow and loud. But this sound
1006 | was not like any I had ever heard. I went to get the binoculars to see if I could spot
1007 | anything. But, no luck. I still kept hearing this low talking sound. I had now totally
1008 | given up weeding. Finding this strange sound was going to be more fun. But where was it
1009 | coming from? I looked again up and down the lake and saw nothing. Finally I went around to
1010 | the other side of the place where we keep our boats. There is an area there where it is
1011 | not a very deep part of the water. I spotted them! It was a mother lake bird and a father
1012 | lake bird with a baby in between them. They were teaching the baby how to swim and eat
1013 | fish. The low talking sound that I heard must have been them trying to teach the baby to
1014 | swim and eat the fish. I sat there on the bank and watched for a half an hour. I felt very
1015 | special that I got to see this. It was such a fun thing to see and way more fun than
1016 | gardening.
1017 | 
1018 | 1: one: What was I doing on this day at the beginning of the story?
1019 |  A) fishing
1020 |  B) sleeping
1021 | *C) working in the garden
1022 |  D) cooking
1023 | 
1024 | 2: one: What did I finally see?
1025 |  A) two lake birds
1026 |  B) four lake birds
1027 | *C) three lake birds
1028 |  D) one lake bird
1029 | 
1030 | 3: multiple: What was the sound that I kept hearing?
1031 |  A) something that sounded like laughing
1032 | *B) something that sounded like low talking
1033 |  C) something that sounded like crying
1034 |  D) something that sounded like singing
1035 | 
1036 | 4: multiple: How did I feel at the end of the story?
1037 | *A) happy
1038 |  B) sick
1039 |  C) sad
1040 |  D) glum
1041 | 
1042 | 
1043 | ***************************************************
1044 | Story:            mc160.dev.23
1045 | Author:           3048636168
1046 | Work Time(s):     1252
1047 | 
1048 | One day Magneson took a walk in the park.  He passed some trees and a pond.  In the pond
1049 | was a duck named George.  George's wife was also in the pond.  Her name was Nancy.
1050 | 
1051 | Magneson walked over to the tree.  Nancy flew up into the tree.  She wanted to warn
1052 | Magneson about the killer squirrel who lived inside of the tree.  A few years before, the
1053 | squirrel had thrown a chestnut at George and Nancy's son.  He was knocked out, and the
1054 | squirrel took him away.  He was never seen again.
1055 | 
1056 | Magneson asked what their son's name was.  They said it was Leonard.  But Magneson was
1057 | only making small talk.  He didn't believe the story about the killer squirrel.  Even if
1058 | there was one, there were many rocks by the pond that he could throw at the squirrel.  He
1059 | could also hide in the tall grass.
1060 | 
1061 | George and Nancy were sorry to see that Magneson wouldn't listen.  They flew away, singing
1062 | a sad song.  A short time later, the squirrel came out of the tree and threw a giant
1063 | walnut at Magneson.  No one ever saw Magneson again.
1064 | 
1065 | 1: multiple: What was George's wife's name?
1066 |  A) Magneson
1067 |  B) George
1068 | *C) Nancy
1069 |  D) Leonard
1070 | 
1071 | 2: multiple: Who did the squirrel throw things at?
1072 |  A) Nellie and George
1073 | *B) Leonard and Magneson
1074 |  C) George and Leonard
1075 |  D) Magneson and Nellie
1076 | 
1077 | 3: one: What did the squirrel throw at Magneson?
1078 |  A) a chestnut
1079 | *B) a giant walnut
1080 |  C) a duck
1081 |  D) a rock
1082 | 
1083 | 4: one: Where did Magneson walk?
1084 |  A) in the trees
1085 |  B) in the pond
1086 | *C) in the park
1087 |  D) in the tall grass
1088 | 
1089 | 
1090 | ***************************************************
1091 | Story:            mc160.dev.24
1092 | Author:           2612134556
1093 | Work Time(s):     2652
1094 | 
1095 | Every Monday morning, the little bad boy named Josh goes to school.
1096 | 
1097 | Suddenly, little Josh slips on a banana skin ...
1098 | 
1099 | - Ouch, says Josh, I fell on this and in addition I got a bump on the forehead!
1100 | 
1101 | - Wonderful! said the banana peel. I am Mary. I turned into banana skin after throwing trash on the school yard. You have saved me and now I'm back to good old Mary. What's your name?
1102 | 
1103 | - Mine is Josh... I'm a late to class ... are you serious, where is the banana peel anyways?
1104 | 
1105 | - The Banana, my dear Josh, was eaten by me, I threw the banana peel and turned into one ... now you saved me, can you see the banana peel you slipped on around here?
1106 | 
1107 | - No, you are right.
1108 | 
1109 | - Mary said:  Josh, Thank you
1110 | 
1111 | - Excuse me, Mary ... I have to go ... Otherwise I'll be late for school ... And I would not want to upset the teacher.
1112 | 
1113 | 1: one: Who slipped on a banana skin?
1114 | *A) Josh
1115 |  B) John
1116 |  C) Mary
1117 |  D) Kate
1118 | 
1119 | 2: multiple: Why Josh was in such a hurry?
1120 |  A) Josh had a soccer game to play.
1121 |  B) Josh was going back home.
1122 |  C) Josh was heading to the school yard.
1123 | *D) Josh was late to class.
1124 | 
1125 | 3: one: Who turned into banana skin after throwing trash on the school yard?
1126 | *A) Mary
1127 |  B) Kate
1128 |  C) Josh
1129 |  D) Peter
1130 | 
1131 | 4: multiple: Who are the principal characters of the story
1132 |  A) Mary and Kate
1133 | *B) Mary and Josh
1134 |  C) Josh and Peter
1135 |  D) Kate and Josh
1136 | 
1137 | 
1138 | ***************************************************
1139 | Story:            mc160.dev.25
1140 | Author:           868073141
1141 | Work Time(s):     5062
1142 | 
1143 | Once there was a young boy named Bret who had a cat named Wolfgang.  The boy had really
1144 | wanted a wolf for a pet, but his mother said wolves liked to hog the bathroom and liked
1145 | to blow things down and they snored.  So the boy had to call his cat Wolfie.
1146 | 
1147 | He had also thought about naming his cat Sir Purrsalot.  Bret himself planned to become a
1148 | knight when he grew up (or maybe a cowboy) and thought Sir Purrsalot sounded like a good
1149 | name for his brother knight.  The difficulty there was that Wolfie didn't purr a lot.  He
1150 | purred when he was being fed or petted, but no one could say he purred a lot.  Plus Bret's
1151 | mother said knights liked to poke things with their swords and they also liked to hog the
1152 | bathroom and they clanked.
1153 | 
1154 | So Bret was left with a cat named Wolfgang.  The neighbors gave him strange looks when he
1155 | stood in the front yard in the evening and yelled "Wolfie!  Here Wolfie!!!", to get
1156 | Wolfgang to come in for the night.  But Bret didn't care what anyone else thought.  He had
1157 | a Wolfie and maybe he'd end up becoming a pet doctor when he grew up instead.
1158 | 
1159 | 1: multiple: When did Wolfie purr?
1160 |  A) when hogging the bathroom
1161 | *B) when petted
1162 |  C) when poked
1163 |  D) when sleeping
1164 | 
1165 | 2: multiple: What was the name of the cat?
1166 |  A) Bret
1167 |  B) Buster
1168 | *C) Wolfgang
1169 |  D) Sir Purrsalot
1170 | 
1171 | 3: one: What was one reasong his mother didn't like knights?
1172 |  A) they grew up
1173 |  B) they purred
1174 |  C) they snored
1175 | *D) they clanked
1176 | 
1177 | 4: one: What was one reason his mother didn't like wolves?
1178 |  A) they yelled
1179 |  B) they barked
1180 |  C) they purred
1181 | *D) they snored
1182 | 
1183 | 
1184 | ***************************************************
1185 | Story:            mc160.dev.26
1186 | Author:           472016790
1187 | Work Time(s):     2027
1188 | 
1189 | Sally liked going outside.  She put on her shoes. She went outside to walk.  She walked on
1190 | the green grass.  The sun was warm.  The trees were tall. The birds sang in the trees.
1191 | Sally liked how the birds can sing.  Sally likes to sing with the birds, outside.  Ring,
1192 | ring, is how the birds sang. Sally sang ring, ring, with the birds in the trees. Sally
1193 | took off her shoes.  Sally liked how the green grass was on her toes.  Sally's toes liked
1194 | the green grass.  Sally walked on the green grass some more.  She saw Missy the cat.
1195 | Missy the cat meowed to Sally.  Sally waved to Missy the cat.  Sally likes Missy the cat.
1196 | Sally likes to meow to Missy the cat.  Meow, meow, Sally says to Missy the cat. Missy the
1197 | cat walks away from Sally.  Sally hears her name.  Sally, Sally, come home, Sally's Mom
1198 | calls out.  Sally runs home to her Mom.  Sally liked going outside.
1199 | 
1200 | 1: multiple: Why did Sally put on her shoes?
1201 |  A) To wave to Missy the cat
1202 |  B) To hear her name
1203 | *C) Because she wanted to go outside
1204 |  D) To come home
1205 | 
1206 | 2: one: What did Sally like to do?
1207 | *A) Sally liked going outside
1208 |  B) walk on the green grass
1209 |  C) put on her shoes
1210 |  D) take off her shoes
1211 | 
1212 | 3: one: What was the name of the cat?
1213 |  A) Meow
1214 | *B) Missy
1215 |  C) Sally
1216 |  D) Ring
1217 | 
1218 | 4: multiple: Who called Sally?
1219 |  A) Missy the cat
1220 |  B) The birds
1221 |  C) The trees
1222 | *D) Her Mom
1223 | 
1224 | 
1225 | ***************************************************
1226 | Story:            mc160.dev.27
1227 | Author:           1429298732
1228 | Work Time(s):     2461
1229 | 
1230 | Tammy likes the park. There are swings at the park. There is a slide at the park.  
1231 | 
1232 | Mary goes to the park with Tammy. They jump rope. They play tag. They like the park.
1233 | 
1234 | Tammy and Mary have fun at the park. Tammy has a dog named Max. Tammy and Mary take Max to the park.
1235 | 
1236 | Max likes the park. He chases rabbits. He chases a ball. Tammy throws the ball to Max. Mary throws the ball to Max.
1237 | 
1238 | The park is no fun in the rain. Tammy and Mary cannot go to the park when it rains. Mother
1239 | says no. They are sad when they cannot go to the park.
1240 | 
1241 | Tammy and Mary play in the house when it rains. They play with dolls. They dress up and
1242 | have a tea party.
1243 | 
1244 | Today is sunny. Tammy and Mary can go to the park. Mother says yes. They can take Max to
1245 | the park. They are happy when it is sunny.
1246 | 
1247 | 1: one: Who has a dog?
1248 |  A) The park
1249 |  B) Max
1250 | *C) Tammy
1251 |  D) Mary
1252 | 
1253 | 2: multiple: What do Tammy and Mary do when it rains?
1254 |  A) go to the park
1255 | *B) Play with dolls, have a tea party
1256 |  C) play ball
1257 |  D) chase rabbits
1258 | 
1259 | 3: multiple: Who likes to go to the park?
1260 |  A) Dolls
1261 |  B) Mother
1262 | *C) Tammy and Mary
1263 |  D) The rabbits
1264 | 
1265 | 4: one: What is the the name of the dog?
1266 |  A) Mother
1267 | *B) Max
1268 |  C) Tammy
1269 |  D) Mary
1270 | 
1271 | 
1272 | ***************************************************
1273 | Story:            mc160.dev.28
1274 | Author:           2345117472
1275 | Work Time(s):     932
1276 | 
1277 | Once upon a time, there was a dog named Puddles. Puddles was lonely because he lived in an
1278 | area where there were no other dogs, but only cats. Day after day, Puddles would have to
1279 | eat cat food and do cat things in order to fit in with the rest of his group. He found it
1280 | very boring and Puddles was sad. Puddles didn't even look like a cat!
1281 | 
1282 | All of the other cats teased Puddles. "You're too big," they said. "You've got too long of
1283 | a nose!" "Why are you panting like that?" Puddles knew that he was different.
1284 | 
1285 | One day, Puddles chose to run away from all of the cats. The cats laughed at him. What a
1286 | stupid dog! Didn't he know that there were monsters in the woods that could eat him?
1287 | Puddles didn't care, because Puddles was sad enough to try.
1288 | 
1289 | So Puddles packed up his things - his squeaky ball, his water dish, and his bone - and
1290 | headed off into the woods. He was finally happy! All of a sudden, Puddles turned. He
1291 | smelled a funny smell. It smelled like something he had never smelled before. He turned
1292 | around, and what did he see but another dog!
1293 | 
1294 | Puddles was so happy, he barked with joy. He went home with the other dog, who was named
1295 | Mittens, and to his family. Puddles was never lonely again.
1296 | 
1297 | 1: multiple: Why did the cats not like him?
1298 |  A) He didn't eat cat food
1299 |  B) He had a long nose
1300 | *C) He was different
1301 |  D) He panted
1302 | 
1303 | 2: one: Where did Puddles live in the beginning?
1304 |  A) with cats and dogs
1305 | *B) In a group of cats
1306 |  C) In a group of dogs
1307 |  D) With humans
1308 | 
1309 | 3: multiple: What does Puddles choose to do?
1310 | *A) Go into the woods
1311 |  B) Go to sleep
1312 |  C) Eat cat food
1313 |  D) Become a cat
1314 | 
1315 | 4: one: Who did Puddles find?
1316 |  A) Food
1317 |  B) A monster
1318 | *C) A dog family
1319 |  D) A group of cats
1320 | 
1321 | 
1322 | ***************************************************
1323 | Story:            mc160.dev.29
1324 | Author:           400332158
1325 | Work Time(s):     839
1326 | 
1327 | Once upon a time there was a princess who lived in a high tower and she was not allowed to
1328 | leave because of her mean mother. One day she chose to leave but her mother would not let
1329 | her. The princess climbed out the window of the high tower and climbed down the south wall
1330 | when her mother was sleeping. She wandered out a good ways. Finally she went into the
1331 | forest where there are no electric poles but where there are some caves.  There she met a
1332 | young man who was running. His name was John. John asked the princess why such a beautiful
1333 | woman like her was out in the middle of a forest. She said that she had been trapped for
1334 | her whole life by an evil woman who said she was her mother. The man said that he would
1335 | take the princess to a castle that was near. He also said that he thought that she may be
1336 | the missing princess. As they go through the forest they run into many problems. They see
1337 | that they are lost and have no way of finding where to go. After several days pass, the
1338 | princess climbs up to the top of a tree in order to find out where they are. She sees that
1339 | the castle where they want to go is not that far away and near a mountain. After thinking
1340 | of the best way to get there, John and the princess go to the castle where they live for
1341 | the rest of their lives.
1342 | 
1343 | 1: multiple: Where did the princess wander to after escaping?
1344 |  A) Mountain
1345 | *B) Forest
1346 |  C) Cave
1347 |  D) Castle
1348 | 
1349 | 2: one: Who escaped from the tower?
1350 |  A) Mother
1351 | *B) Princess
1352 |  C) Man
1353 |  D) John
1354 | 
1355 | 3: multiple: What did the princess climb to see the castle?
1356 |  A) Electric pole
1357 |  B) mountain
1358 | *C) Tree
1359 |  D) Castle
1360 | 
1361 | 4: one: Where does the princess live in the beginning?
1362 |  A) Castle
1363 |  B) house
1364 |  C) Cave
1365 | *D) High Tower
1366 | 
1367 | 
1368 | 


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