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arXiv · 2004.15016

WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context

Anna Breit·Artem Revenko·Kiamehr Rezaee·Mohammad Taher Pilehvar·Jose Camacho-Collados
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Abstract

We present WiC-TSV, a new multi-domain evaluation benchmark for Word Sense Disambiguation. More specifically, we introduce a framework for Target Sense Verification of Words in Context which grounds its uniqueness in the formulation as a binary classification task thus being independent of external sense inventories, and the coverage of various domains. This makes the dataset highly flexible for the evaluation of a diverse set of models and systems in and across domains. WiC-TSV provides three different evaluation settings, depending on the input signals provided to the model. We set baseline performance on the dataset using state-of-the-art language models. Experimental results show that even though these models can perform decently on the task, there remains a gap between machine and human performance, especially in out-of-domain settings. WiC-TSV data is available at https://competitions.codalab.org/competitions/23683

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Anna Breit, Artem Revenko, Kiamehr Rezaee, Mohammad Taher Pilehvar, Jose Camacho-Collados. 2020-04-30. WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context. https://arxiv.org/abs/2004.15016

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