@inproceedings{kannan-santhi-ponnusamy-2020-tukapo,
title = {{T}{\"u}{K}a{P}o at {S}em{E}val-2020 Task 6: Def(n)tly Not {BERT}: Definition Extraction Using pre-{BERT} Methods in a post-{BERT} World},
author = "Kannan, Madeeswaran and
Santhi Ponnusamy, Haemanth",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.95",
doi = "10.18653/v1/2020.semeval-1.95",
pages = "724--729",
abstract = {We describe our system (T{\"u}KaPo) submitted for Task 6: DeftEval, at SemEval 2020. We developed a hybrid approach that combined existing CNN and RNN methods and investigated the impact of purely-syntactic and semantic features on the task of definition extraction. Our final model achieved a F1-score of 0.6851 in subtask 1, i.e, sentence classification.},
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="kannan-santhi-ponnusamy-2020-tukapo">
<titleInfo>
<title>TüKaPo at SemEval-2020 Task 6: Def(n)tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World</title>
</titleInfo>
<name type="personal">
<namePart type="given">Madeeswaran</namePart>
<namePart type="family">Kannan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Haemanth</namePart>
<namePart type="family">Santhi Ponnusamy</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2020-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Fourteenth Workshop on Semantic Evaluation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Aurelie</namePart>
<namePart type="family">Herbelot</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Xiaodan</namePart>
<namePart type="family">Zhu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alexis</namePart>
<namePart type="family">Palmer</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nathan</namePart>
<namePart type="family">Schneider</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jonathan</namePart>
<namePart type="family">May</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ekaterina</namePart>
<namePart type="family">Shutova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>International Committee for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Barcelona (online)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>We describe our system (TüKaPo) submitted for Task 6: DeftEval, at SemEval 2020. We developed a hybrid approach that combined existing CNN and RNN methods and investigated the impact of purely-syntactic and semantic features on the task of definition extraction. Our final model achieved a F1-score of 0.6851 in subtask 1, i.e, sentence classification.</abstract>
<identifier type="citekey">kannan-santhi-ponnusamy-2020-tukapo</identifier>
<identifier type="doi">10.18653/v1/2020.semeval-1.95</identifier>
<location>
<url>https://aclanthology.org/2020.semeval-1.95</url>
</location>
<part>
<date>2020-12</date>
<extent unit="page">
<start>724</start>
<end>729</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T TüKaPo at SemEval-2020 Task 6: Def(n)tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World
%A Kannan, Madeeswaran
%A Santhi Ponnusamy, Haemanth
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F kannan-santhi-ponnusamy-2020-tukapo
%X We describe our system (TüKaPo) submitted for Task 6: DeftEval, at SemEval 2020. We developed a hybrid approach that combined existing CNN and RNN methods and investigated the impact of purely-syntactic and semantic features on the task of definition extraction. Our final model achieved a F1-score of 0.6851 in subtask 1, i.e, sentence classification.
%R 10.18653/v1/2020.semeval-1.95
%U https://aclanthology.org/2020.semeval-1.95
%U https://doi.org/10.18653/v1/2020.semeval-1.95
%P 724-729
Markdown (Informal)
[TüKaPo at SemEval-2020 Task 6: Def(n)tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World](https://aclanthology.org/2020.semeval-1.95) (Kannan & Santhi Ponnusamy, SemEval 2020)
ACL