Exploiting Open IE for Deriving Multiple Premises Entailment Corpus

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00110584" target="_blank" >RIV/00216224:14330/19:00110584 - isvavai.cz</a>

Výsledek na webu

<a href="http://lml.bas.bg/ranlp2019/proceedings-ranlp-2019.pdf" target="_blank" >http://lml.bas.bg/ranlp2019/proceedings-ranlp-2019.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.26615/978-954-452-056-4_144" target="_blank" >10.26615/978-954-452-056-4_144</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Exploiting Open IE for Deriving Multiple Premises Entailment Corpus

Popis výsledku v původním jazyce

Natural language inference (NLI) is a key part of natural language understanding. The NLI task is defined as a decision problem whether a given sentence -- hypothesis -- can be inferred from a given text. Typically, we deal with a text consisting of just a single premise/single sentence, which is called a single premise entailment (SPE) task. Recently, a derived task of NLI from multiple premises (MPE) was introduced together with the first annotated corpus and corresponding several strong baselines. Nevertheless, the further development in MPE field requires accessibility of huge amounts of annotated data. In this paper we introduce a novel method for rapid deriving of MPE corpora from an existing NLI (SPE) annotated data that does not require any additional annotation work. This proposed approach is based on using an open information extraction system. We demonstrate the application of the method on a well known SNLI corpus. Over the obtained corpus, we provide the first evaluations as well as we state a strong baseline.

Název v anglickém jazyce

Exploiting Open IE for Deriving Multiple Premises Entailment Corpus

Popis výsledku anglicky

Natural language inference (NLI) is a key part of natural language understanding. The NLI task is defined as a decision problem whether a given sentence -- hypothesis -- can be inferred from a given text. Typically, we deal with a text consisting of just a single premise/single sentence, which is called a single premise entailment (SPE) task. Recently, a derived task of NLI from multiple premises (MPE) was introduced together with the first annotated corpus and corresponding several strong baselines. Nevertheless, the further development in MPE field requires accessibility of huge amounts of annotated data. In this paper we introduce a novel method for rapid deriving of MPE corpora from an existing NLI (SPE) annotated data that does not require any additional annotation work. This proposed approach is based on using an open information extraction system. We demonstrate the application of the method on a well known SNLI corpus. Over the obtained corpus, we provide the first evaluations as well as we state a strong baseline.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of Recent Advances in Natural Language Processing

ISBN

9789544520557

ISSN

2603-2813

e-ISSN

1313-8502

Počet stran výsledku

8

Strana od-do

1257-1264

Název nakladatele

2019

Místo vydání

Varna

Místo konání akce

Varna

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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