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arXiv 2102.00395cs.CLcs.AI

An Unsupervised Language-Independent Entity Disambiguation Method and its Evaluation on the English and Persian Languages

Iran University of Science and Technology(伊朗科技大学)

Majid Asgari-Bidhendi, Behrooz Janfada, Amir Havangi, Sayyed Ali Hossayni, Behrouz Minaei-Bidgoli

英文摘要:

Entity Linking is one of the essential tasks of information extraction and natural language understanding. Entity linking mainly consists of two tasks: recognition and disambiguation of named entities. Most studies address these two tasks separately or focus only on one of them. Moreover, most of the state-of-the -art entity linking algorithms are either supervised, which have poor performance in the absence of annotated corpora or language-dependent, which are not appropriate for multi-lingual applications. In this paper, we introduce an Unsupervised Language-Independent Entity Disambiguation (ULIED), which utilizes a novel approach to disambiguate and link named entities. Evaluation of ULIED on different English entity linking datasets as well as the only available Persian dataset illustrates that ULIED in most of the cases outperforms the state-of-the-art unsupervised multi-lingual approaches.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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