WiC-TSV:上下文环境中单词目标义验证的评价基准（CS.CL）---用户7236395

在本文中，我们提出了一种新的多领域词义消歧(WSD)和实体链接(EL)的评价基准——WiC-TSV (textit{Target Sense Verification for Words in Context})。我们的基准测试与传统的词义消歧及实体链接基准测试不同，因为它是独立于一般意义的库存，因此在评估不同范畴的不同模型及系统时，具有高度的灵活性。WiC-TSV分为三个任务(系统得到关于目标感觉的夸张的信息，或定义的信息，或同时得到关于目标感觉的夸张和定义的信息)。测试数据可用于四个领域:通用(WordNet)、计算机科学、鸡尾酒和医学概念。结果表明，现有的语言模型，如BERT模型，在域内数据和域外数据方面都能达到较高的性能，但仍有改进的空间。WiC-TSV任务数据在url{ this https url}中可用。

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

原文：In this paper, we present WiC-TSV (textit{Target Sense Verification for Words in Context}), a new multi-domain evaluation benchmark for Word Sense Disambiguation (WSD) and Entity Linking (EL). Our benchmark is different from conventional WSD and EL benchmarks for it being independent of a general sense inventory, making it highly flexible for the evaluation of a diverse set of models and systems in different domains. WiC-TSV is split into three tasks (systems get hypernymy or definitional or both hypernymy and definitional information about the target sense). Test data is available in four domains: general (WordNet), computer science, cocktails and medical concepts. Results show that existing state-of-the-art language models such as BERT can achieve a high performance in both in-domain data and out-of-domain data, but they still have room for improvement. WiC-TSV task data is available at url{this https URL}.

原文作者：Anna Breit, Artem Revenko, Kiamehr Rezaee, Mohammad Taher Pilehvar, Jose Camacho-Collados

原文地址：https://arxiv.org/abs/2004.15016