├── .gitignore ├── .travis.yml ├── LICENSE ├── README.md ├── bella ├── __init__.py ├── contexts.py ├── data_types.py ├── dependency_parsers.py ├── dependency_tokens.py ├── error_analysis.py ├── evaluation.py ├── helper.py ├── lexicons.py ├── models │ ├── __init__.py │ ├── base.py │ ├── target.py │ ├── tdlstm.py │ └── tdparse.py ├── moses_tools.py ├── neural_pooling.py ├── parsers.py ├── scikit_features │ ├── __init__.py │ ├── context.py │ ├── debug.py │ ├── join_context_vectors.py │ ├── lexicon_filter.py │ ├── neural_pooling.py │ ├── syntactic_context.py │ ├── tokeniser.py │ └── word_vector.py ├── stanford_tools.py ├── syntactic_contexts.py ├── tokenisers.py ├── word_vectors.py └── write_data.py ├── config.yaml ├── docs ├── Makefile ├── conf.py ├── index.rst └── make.bat ├── notebooks ├── LSTM.ipynb ├── Mass Evaluation - TDParse.ipynb ├── Mass Evaluation - Target Dependent.ipynb ├── Mass Evaluation LSTM.ipynb ├── Mass Evaluation Result Analysis.ipynb ├── Mitchel et al dataset splitting.ipynb ├── Model Example.ipynb ├── Pre-Trained Model Example.ipynb ├── TDParse.ipynb ├── YouTuBean dataset splitting.ipynb ├── datasets.ipynb ├── target_model.ipynb └── tdparse_parser.ipynb ├── pytest.ini ├── requirements.txt ├── results ├── TDLstm │ ├── LSTM │ │ ├── LSTM glove twitter 100d Repeated Results.json │ │ ├── LSTM glove twitter 200d Repeated Results.json │ │ ├── LSTM glove twitter 50d Repeated Results.json │ │ ├── LSTM sswe Repeated Results.json │ │ ├── dataset predictions.json │ │ └── word vectors.json │ ├── TCLSTM │ │ ├── TCLSTM glove twitter 100d Repeated Results.json │ │ ├── TCLSTM glove twitter 200d Repeated Results.json │ │ ├── TCLSTM glove twitter 50d Repeated Results.json │ │ ├── TCLSTM sswe Repeated Results.json │ │ ├── dataset predictions.json │ │ └── word vectors.json │ └── TDLSTM │ │ ├── TDLSTM glove twitter 100d Repeated Results.json │ │ ├── TDLSTM glove twitter 200d Repeated Results.json │ │ ├── TDLSTM glove twitter 50d Repeated Results.json │ │ ├── TDLSTM sswe Repeated Results.json │ │ ├── dataset predictions.json │ │ └── word vectors.json ├── TDParse │ ├── Dong Twitter Best C.json │ ├── Election Twitter Best C.json │ ├── Mass Evaluation Best C.json │ ├── Mass Evaluation Best Embedding.json │ ├── TDParse │ │ └── dataset predictions.json │ └── TDParsePlus │ │ └── dataset predictions.json └── Target Dependent │ ├── Mass Evaluation Best C.json │ ├── Mass Evaluation Best Embedding.json │ ├── Target Dependent Plus │ └── dataset predictions.json │ └── Target Dependent │ └── dataset predictions.json ├── setup.py └── tests ├── test_contexts.py ├── test_data ├── dong_test_bad_sent_data.txt ├── dong_test_data.txt ├── dong_test_multiple_offsets_data.txt ├── dong_test_mwe_offsets_data.txt ├── semeval_test_data.xml └── sherlock_holmes.txt ├── test_data_types.py ├── test_dependency_parsers.py ├── test_dependency_tokens.py ├── test_helper.py ├── test_lexicons.py ├── test_neural_pooling.py ├── test_parsers.py ├── test_syntactic_contexts.py ├── 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