A Graph-based Approach for Persian Entity Linking
Publish place: International Journal of Information and Communication Technology Research (IJICT، Vol: 12، Issue: 3
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_ITRC-12-3_006
تاریخ نمایه سازی: 14 فروردین 1401
Abstract:
Most of the data on the web is in the form of natural language, but natural language is highly ambiguous, especially when it comes to the frequent occurrence of entities. The goal of entity linking is to find entity mentions and link them to their corresponding entities in an external knowledge base. Recently, FarsBase was introduced as the first Persian knowledge base with nearly ۷۵۰,۰۰۰ entities. This research suggested one of the first end-to-end unsupervised entity linking systems specifically for Persian, using context and graph-based features to rank candidate entities. To evaluate the proposed method, we used the first Persian entity-linking dataset created by crawling social media text from some popular Telegram channels. The ParsEL results show that the F-Score of the input data set is ۸۷.۱% and is comparable to any other entity-linking system that supports Persian.
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Authors
Majid Asgari-Bidhendi
Computer Engineering School Iran University of Science and Technology Tehran, Iran
Farzane Fakhrian
Computer Engineering School Iran University of Science and Technology Tehran, Iran
Behrouz Minaei-Bidgoli
Computer Engineering School Iran University of Science and Technology Tehran, Iran