文章基本信息

标题：Retrieval, Re-ranking and Multi-task Learning for Knowledge-Base Question Answering
本地全文：下载
作者：Zhiguo Wang ; Patrick Ng ; Ramesh Nallapati 等
期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2021
卷号：2021
页码：347-357
DOI：10.18653/v1/2021.eacl-main.26
语种：English
出版社：ACL Anthology
摘要：Question answering over knowledge bases (KBQA) usually involves three sub-tasks, namely topic entity detection, entity linking and relation detection. Due to the large number of entities and relations inside knowledge bases (KB), previous work usually utilized sophisticated rules to narrow down the search space and managed only a subset of KBs in memory. In this work.