Alias Identification from Narratives for Question Answering

5 Pages Posted: 25 Aug 2019

See all articles by Fahma Bakkar

Fahma Bakkar

Government Engineering College, Palakkad, Department of Computer Science and Engineering, Students

Rafeeque

Government College of Engineering Kannur

Reena

Government College of Engineering Kannur

Date Written: August 22, 2019

Abstract

Alias is the term used to give a person’s name after giving his or her real name. The name can be Pronouns or Generic (Noun Phrases) NPs. For identifying pronouns co-reference resolution is being used. Identifying Generic NPs from a narrative is a crucial task, because we observed that standard Natural Language Processing (NLP) tool-kits work poorly for generic NPs. NLP applications using the co-reference resolution technique are Timeline creation, Question-answering, Summarization and Information extraction. In this work, we propose an approach using linguistic knowledge for Alias Identification and Question Answering system to answer the given question. For encoding the linguistic knowledge Markov Logic Network (MLN) is used. The proposed system is a combination of Alias Identification and a Question Answering. Public narratives/paragraph of varying linguistic complexity is selected as input to the alias identification system. Input to the question answering system is output alias identification system and question. From the narratives/paragraph answers to the corresponding questions will be extracted. The system generates the answer sentence by finding the first pronoun or generic NP which is replaced with canonical form.

Keywords: Co-reference resolution, Natural Language Processing (NLP), Markov Logic Network (MLN)

Suggested Citation

K A, Fahma Bakkar and P C, Rafeeque and Murali, Reena, Alias Identification from Narratives for Question Answering (August 22, 2019). In proceedings of the International Conference on Systems, Energy & Environment (ICSEE) 2019, GCE Kannur, Kerala, July 2019. Available at SSRN: https://ssrn.com/abstract=3441328 or http://dx.doi.org/10.2139/ssrn.3441328

Fahma Bakkar K A (Contact Author)

Government Engineering College, Palakkad, Department of Computer Science and Engineering, Students ( email )

India

Rafeeque P C

Government College of Engineering Kannur ( email )

Kannur
India

Reena Murali

Government College of Engineering Kannur ( email )

Kannur
India

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