@inproceedings{perera-nand-2016-answer,
title = "Answer Presentation in Question Answering over Linked Data using Typed Dependency Subtree Patterns",
author = "Perera, Rivindu and
Nand, Parma",
editor = "Choi, Key-Sun and
Unger, Christina and
Vossen, Piek and
Kim, Jin-Dong and
Kando, Noriko and
Ngonga Ngomo, Axel-Cyrille",
booktitle = "Proceedings of the Open Knowledge Base and Question Answering Workshop ({OKBQA} 2016)",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/W16-4406",
pages = "44--48",
abstract = "In an era where highly accurate Question Answering (QA) systems are being built using complex Natural Language Processing (NLP) and Information Retrieval (IR) algorithms, presenting the acquired answer to the user akin to a human answer is also crucial. In this paper we present an answer presentation strategy by embedding the answer in a sentence which is developed by incorporating the linguistic structure of the source question extracted through typed dependency parsing. The evaluation using human participants proved that the methodology is human-competitive and can result in linguistically correct sentences for more that 70{\%} of the test dataset acquired from QALD question dataset.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="perera-nand-2016-answer">
<titleInfo>
<title>Answer Presentation in Question Answering over Linked Data using Typed Dependency Subtree Patterns</title>
</titleInfo>
<name type="personal">
<namePart type="given">Rivindu</namePart>
<namePart type="family">Perera</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Parma</namePart>
<namePart type="family">Nand</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2016-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Open Knowledge Base and Question Answering Workshop (OKBQA 2016)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Key-Sun</namePart>
<namePart type="family">Choi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Christina</namePart>
<namePart type="family">Unger</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Piek</namePart>
<namePart type="family">Vossen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jin-Dong</namePart>
<namePart type="family">Kim</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Noriko</namePart>
<namePart type="family">Kando</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Axel-Cyrille</namePart>
<namePart type="family">Ngonga Ngomo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>The COLING 2016 Organizing Committee</publisher>
<place>
<placeTerm type="text">Osaka, Japan</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>In an era where highly accurate Question Answering (QA) systems are being built using complex Natural Language Processing (NLP) and Information Retrieval (IR) algorithms, presenting the acquired answer to the user akin to a human answer is also crucial. In this paper we present an answer presentation strategy by embedding the answer in a sentence which is developed by incorporating the linguistic structure of the source question extracted through typed dependency parsing. The evaluation using human participants proved that the methodology is human-competitive and can result in linguistically correct sentences for more that 70% of the test dataset acquired from QALD question dataset.</abstract>
<identifier type="citekey">perera-nand-2016-answer</identifier>
<location>
<url>https://aclanthology.org/W16-4406</url>
</location>
<part>
<date>2016-12</date>
<extent unit="page">
<start>44</start>
<end>48</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Answer Presentation in Question Answering over Linked Data using Typed Dependency Subtree Patterns
%A Perera, Rivindu
%A Nand, Parma
%Y Choi, Key-Sun
%Y Unger, Christina
%Y Vossen, Piek
%Y Kim, Jin-Dong
%Y Kando, Noriko
%Y Ngonga Ngomo, Axel-Cyrille
%S Proceedings of the Open Knowledge Base and Question Answering Workshop (OKBQA 2016)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F perera-nand-2016-answer
%X In an era where highly accurate Question Answering (QA) systems are being built using complex Natural Language Processing (NLP) and Information Retrieval (IR) algorithms, presenting the acquired answer to the user akin to a human answer is also crucial. In this paper we present an answer presentation strategy by embedding the answer in a sentence which is developed by incorporating the linguistic structure of the source question extracted through typed dependency parsing. The evaluation using human participants proved that the methodology is human-competitive and can result in linguistically correct sentences for more that 70% of the test dataset acquired from QALD question dataset.
%U https://aclanthology.org/W16-4406
%P 44-48
Markdown (Informal)
[Answer Presentation in Question Answering over Linked Data using Typed Dependency Subtree Patterns](https://aclanthology.org/W16-4406) (Perera & Nand, 2016)
ACL