Show simple item record

dc.contributor.authorPeng, Zhongyu 17:07:03 (GMT) 17:07:03 (GMT)
dc.description.abstractWe present a novel bag-of-words based approach that automatically constructs a semantic parsing based question answering (QA) system tailored to single-entity-single-relation questions. Given a large community QA pair corpus and a knowledge base, our approach uses knowledge base entries to supervise relation extraction from the corpus, reduces noise in the extracted data via unsupervised clustering, and learns to identify each relation’s question patterns. We implement the approach on a large Chinese corpus with little annotation, which we believe is one of the first of its kind. Experiments show that our implementation manages to answer questions in test cases independent of the corpus with relatively high accuracy and to avoid answering questions beyond its scope, achieving a high accuracy on answered questions.en
dc.publisherUniversity of Waterlooen
dc.titleSingle-Entity-Single-Relation Question Answering with Minimal Annotationen
dc.typeMaster Thesisen
dc.pendingfalse R. Cheriton School of Computer Scienceen Scienceen of Waterlooen
uws-etd.degreeMaster of Mathematicsen
uws.contributor.advisorLi, Ming
uws.contributor.affiliation1Faculty of Mathematicsen

Files in this item


This item appears in the following Collection(s)

Show simple item record


University of Waterloo Library
200 University Avenue West
Waterloo, Ontario, Canada N2L 3G1
519 888 4883

All items in UWSpace are protected by copyright, with all rights reserved.

DSpace software

Service outages