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This repository contains the CONTEXT-WN dataset described in the *SEM 2017 Paper, Detecting Asymmetric Semantic Relations in Context : A Case Study on Hypernymy Detection.
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The data has been split into a train, dev, and test set. The same split has been used in the experiments reported in the paper.
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The data is in a tab seperated format with 4 columns. Each row is a single example of the type (c_l,w_l,c_r,w_r) with the columns as follows :
- c_l = left context
- w_l = left word
- c_r = right context
- w_r = right word
- Entailment label - 0 = False, 1 = True
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The data is already tokenized and lowercased
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The data is available under the CC BY-SA 4.0 license. If you use the data, please cite our paper:
@inproceedings{VyasCarpuat2017, address = {{Vancouver, Canada}}, title = {Detecting {{Asymmetric Semantic Relations}} in {{Context}}: {{A Case}}-{{Study}} on {{Hypernymy Detection}}}, shorttitle = {Detecting {{Asymmetric Semantic Relations}} in {{Context}}}, booktitle = {Proceedings of the 6th {{Joint Conference}} on {{Lexical}} and {{Computational Semantics}} (*{{SEM}} 2017)}, publisher = {{Association for Computational Linguistics}}, doi = {10.18653/v1/S17-1004}, author = {Vyas, Yogarshi and Carpuat, Marine}, month = aug, year = {2017}, pages = {33--43}, }
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Data from the *SEM 2017 Paper
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