First Steps in Recognizing Relational Entailment – Experimental Corpus and Baselines

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

First Steps in Recognizing Relational Entailment – Experimental Corpus and Baselines

Popis výsledku v původním jazyce

Recently, a task of recognizing relational entailment (RRE) was introduced as a task to decide whether the meaning of a given textual $n$-tuple $t$, i. e., the semantic relationship expressed by $t$, can be inferred from a given text $T$. Since then-tuples are obtained from theopen information extraction process, this task naturally connects two NLP fields: natural language inference (NLI) and open information extraction (open IE). The task has a “practical” counterpart: checking/proving facts stored in open knowledge bases. However, no corresponding annotated corpus has been available yet as well as baselines for this task. In this paper, we present a corpus derived fromthe well known SNLI corpus and provide baselines based on LSTM architectures and state also a baseline using “hypothesis-only”-like approach.

Název v anglickém jazyce

First Steps in Recognizing Relational Entailment – Experimental Corpus and Baselines

Popis výsledku anglicky

Recently, a task of recognizing relational entailment (RRE) was introduced as a task to decide whether the meaning of a given textual $n$-tuple $t$, i. e., the semantic relationship expressed by $t$, can be inferred from a given text $T$. Since then-tuples are obtained from theopen information extraction process, this task naturally connects two NLP fields: natural language inference (NLI) and open information extraction (open IE). The task has a “practical” counterpart: checking/proving facts stored in open knowledge bases. However, no corresponding annotated corpus has been available yet as well as baselines for this task. In this paper, we present a corpus derived fromthe well known SNLI corpus and provide baselines based on LSTM architectures and state also a baseline using “hypothesis-only”-like approach.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

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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

Human Language Technologies as a Challenge for Computer Science and Linguistics – 2019

ISBN

9788365988317

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

143-147

Název nakladatele

Wydawnictwo Nauka i Innowacje

Místo vydání

Poznań

Místo konání akce

Poznań

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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