WHiC

• 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.

• 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.

• 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 :

  1. c_l = left context
  2. w_l = left word
  3. c_r = right context
  4. w_r = right word
  5. Entailment label - 0 = False, 1 = True

• The data is already tokenized and lowercased

• 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},
  }