Published March 11, 2020
| Version v1
Dataset
Open
Word-in-Context Target Sense Verification
- 1. Semantic Web Company
- 2. Cardiff University, United Kingdom
- 3. ran University of Science and Technology
- 4. Tehran Institute for Advanced Studies, Iran
Description
Formally, WiC is framed as a binary classification task. Each instance in WiC-TSV consists of a target word w with a corresponding target sense s represented by either its definition (subtask 1) or its hypernym/s (subtask 2), and a context c containing the target word w. The task aims to determine whether the meaning of the word w used in the context c matches the target sense s. In the following table there are some examples from the dataset.
Subtasks
WiC-TSV has three subtasks - participants can submit results in any of the subtasks:
Subtask 1: Definitions
In Subtask 1 systems make use of definitions for deciding whether the target word in context corresponds to the given definition or not.
Subtask 2: Hypernyms
In Subtask 2 systems make use of hypernymy information for deciding whether the target word in context is a hyponym of the given hypernym or not.
Subtask 3: Definitions + Hypernyms
In subtask 3 systems can make use of both sources of information, i.e., definitions and hypernyms.
Notes
Latest updates to the dataset and the models are available in this repository: https://github.com/semantic-web-company/wic-tsv
Files
WICTSV.zip
Files
(295.5 kB)
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Additional details
Related works
- Is previous version of
- Dataset: https://github.com/semantic-web-company/wic-tsv (URL)
Funding
References
- Anna Breit, Artem Revenko, Kiamehr Rezaee, Mohammad Taher Pilehvar and Jose Camacho-Collados (2020) WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context, arXiv preprint arXiv:2004.15016