├── jbirke_thesis.pdf ├── Presentation_EACL06.ppt ├── TroFi_Figures ├── Figure10-A.pdf ├── Figure10-B.pdf ├── Figure7-A.pdf ├── Figure7-B.pdf ├── Figure7-C.pdf ├── Figure7-D.pdf ├── Figure7-F.pdf ├── Figure7-G.pdf ├── Figure7-L.pdf ├── Figure7-M.pdf ├── Figure8-A.pdf ├── Figure8-D.pdf ├── Figure8-E.pdf ├── Figure8-F.pdf ├── Figure8-G.pdf ├── Figure8-I.pdf ├── Figure8-J.pdf ├── Figure9-A.pdf ├── Figure9-C.pdf ├── Figure9-E.pdf ├── Figure9-F.pdf ├── Figure7-E-a.pdf ├── Figure7-E-b.pdf ├── Figure7-H-a.pdf ├── Figure7-H-b.pdf ├── Figure7-I-a.pdf ├── Figure7-I-b.pdf ├── Figure7-J-a.pdf ├── Figure7-J-b.pdf ├── Figure7-K-a.pdf ├── Figure7-K-b.pdf ├── Figure8-B-a.pdf ├── Figure8-B-b.pdf ├── Figure8-B-c.pdf ├── Figure8-B-d.pdf ├── Figure8-C-a.pdf ├── Figure8-C-b.pdf ├── Figure8-H-a.pdf ├── Figure8-H-b.pdf ├── Figure9-B-a.pdf ├── Figure9-B-b.pdf ├── Figure9-B-c.pdf ├── Figure9-D-a.pdf └── Figure9-D-b.pdf ├── LICENSE.html └── README.md /jbirke_thesis.pdf: 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2 |

LICENSE

3 |
4 | 5 |
6 |

TroFi Example Base 7 |

All rights reserved. 8 |

(c) 2005 Julia Birke 9 |

Constructed by Julia Birke 10 |
Simon Fraser University 11 |
School of Computing Science 12 |
8888 University Drive 13 |
Vancouver BC V6B 5K3 14 |
Canada 15 | 16 |

17 | 18 |

19 | LICENSE INFORMATION 20 | 21 |

22 | Julia Birke ("Owner") 23 | grants to the individual researcher who downloads this 24 | Example Base ("Licensee") a non-exclusive, non-transferable 25 | license to use the TroFi Example Base ("Example Base"), 26 | subject to the restrictions listed below under "Scope of Grant." 27 | 28 | The Example Base contains content from The 1987-89 Wall Street 29 | Journal (WSJ) Corpus Release 1 ("Corpus") licensed through 30 | the Linguistic Data Consortium. To copy all or part of 31 | the Example Base, in accordance with the restrictions listed 32 | below under "Scope of Grant", the Licensee must hold a valid 33 | Linguistic Data Consurtium license. 34 | 35 | 36 |

37 | SCOPE OF GRANT 38 |

39 | The Licensee may: 40 |

46 | 47 |

48 | The Licensee may not: 49 |

57 | 58 |

59 | DISCLAIMER 60 | 61 |

62 | The Owner makes no representations or warranties about the suitability of the 63 | Example Base, either express or implied, including but 64 | not limited to the implied warranties of merchantability, fitness for a 65 | particular purpose, or non-infringement. The Owner shall not be liable for 66 | any damages suffered by Licensee as a result of using, modifying or 67 | distributing the Example Base or its derivatives. 68 | 69 |

70 | CONSENT 71 |

72 | By downloading, using or copying the Example Base, Licensee 73 | agrees to abide by the intellectual property laws, and all other 74 | applicable laws of the U.S. and Canada, and the terms of this License. Ownership of the Example Base shall remain solely with the Owner. 75 | 76 |

77 | TERMINATION 78 |

79 | The Owner shall have the right to terminate this license at any time by written 80 | notice. Licensee shall be liable for any infringement or damages resulting 81 | from Licensee's failure to abide by the terms of this License. 82 | 83 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # TroFi Metaphor Dataset 2 | 3 | Begin3 4 | Title: TroFi Example Base 5 | Version: 1.0 6 | Entered-date: 11 July 2005 7 | Description: A database of literal/nonliteral sentence clusters for 50 words 8 | Keywords: clustering nonliteral metaphor nlp 9 | Author: Julia Birke 10 | Maintained-by: Anoop Sarkar 11 | Home-page: http://natlang.cs.sfu.ca/ 12 | Alternate-site: 13 | Primary-site: http://natlang.cs.sfu.ca/software/trofi.html 14 | Platform: 15 | Copying-policy: GPL 16 | End3 17 | 18 | ## Data: 19 | 20 | * [TroFi Example Base](TroFiExampleBase.txt) 21 | 22 | If you use this data, please cite the following paper(s): 23 | 24 | * [Clustering Approach for the Nearly Unsupervised Recognition of Nonliteral Language](http://aclweb.org/anthology/E/E06/E06-1042.pdf). Julia Birke and Anoop Sarkar. In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics, EACL-2006. Trento, Italy. April 3-7, 2006. 25 | * [Active Learning for the Identification of Nonliteral Language](http://aclweb.org/anthology/W/W07/W07-0104.pdf). Julia Birke and Anoop Sarkar. In Proceedings of the Workshop on Computational Approaches to Figurative Language, NAACL-HLT 2007 workshop. Rochester, NY. April 26, 2007. 26 | 27 | Before installing please read the contents of the [LICENSE](LICENSE.html) file that accompanies this distribution. 28 | 29 | ## General Description: 30 | 31 | The TroFi Example Base consists of literal and nonliteral usage clusters for 50 English verbs. The clusters contain sentences using these words drawn from The 1987-89 Wall Street Journal (WSJ) Corpus Release 1. The clusters were automatically generated using TroFi, a system for the unsupervised recognition of nonliteral language. For detailed information on the TroFi Example Base and the system used to produce it, please see: 32 | 33 | * Birke, J. 2005. [A clustering approach for the unsupervised recognition of nonliteral language](jbirke_thesis.pdf). Masters Thesis. School of Computing Science. Simon Fraser University. 34 | * [EACL 2006 Presentation Slides](Presentation_EACL06.ppt) 35 | 36 | ## Contents: 37 | 38 | The TroFi Example Base contains literal/nonliteral clusters for the following words: 39 | 40 | | | | | | | 41 | |------------|-------------|----------|----------|----------| 42 | | absorb | drink | flow | pass | sleep | 43 | | assault | drown | fly | plant | smooth | 44 | | attack | eat | grab | play | step | 45 | | besiege | escape | grasp | plow | stick | 46 | | cool | evaporate | kick | pour | strike | 47 | | dance | examine | kill | pump | stumble | 48 | | destroy | fill | knock | rain | target | 49 | | die | fix | lend | rest | touch | 50 | | dissolve | flood | melt | ride | vaporize | 51 | | drag | flourish | miss | roll | wither | 52 | ------------------------------------------------------------- 53 | 54 | Average accuracy is estimated at approximately 64%. 55 | 56 | 57 | ## Structure: 58 | 59 | The TroFi Example Base is organized by the target words listed above. Under each target word, first the nonliteral cluster, then the literal cluster, is given. The order of the examples is dependent on the TroFi run in which they were clustered. The examples from the original run are given first, in numerical order; the examples from the iterative augmentation run are given next. (See [Birke, 2005](jbirke_thesis.pdf)) 60 | 61 | The examples contain three tab-delimited columns. 62 | 63 | The first column contains an identifier to link the sentence back to the WSJ source files used by TroFi. For TroFi, the WSJ sentences were split into 86 files. In an identifier, for example wsj02:2251, the first number is the file number; the second, the line within that file. 64 | 65 | The second column contains one of three labels for the status of human annotation: L (Literal), N (Nonliteral), or U (Unannotated). There are two reasons a sentence may have an annotation of L or N. For the first run, all the sentences were manually annotated for testing purposes. For the iterative augmentation run, only those sentences that were sent to the human for active learning (Birke, 2005) will have an L or N label. All other sentences have a U label for "Unannotated". 66 | 67 | The third column is the tokenized WSJ sentence. Each sentence ends with "./." 68 | 69 | For example: 70 | 71 | ***absorb*** 72 | *nonliteral cluster* 73 | wsj02:2251 U Another option will be to try to curb the growth in education and other local assistance , which absorbs 66 % of the state 's budget ./. 74 | wsj03:2839 N But in the short-term it will absorb a lot of top management 's energy and attention , '' says Philippe Haspeslagh , a business professor at the European management school , Insead , in Paris ./. 75 | *literal cluster* 76 | wsj11:1363 L An Energy Department spokesman says the sulfur dioxide might be simultaneously recoverable through the use of powdered limestone , which tends to absorb the sulfur ./. 77 | 78 | --------------------------------------------------------------------------------