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First Steps in Recognizing Relational Entailment – Experimental Corpus and Baselines

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00110583" target="_blank" >RIV/00216224:14330/19:00110583 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    First Steps in Recognizing Relational Entailment – Experimental Corpus and Baselines

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

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

  • ISBN

    9788365988317

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    143-147

  • Publisher name

    Wydawnictwo Nauka i Innowacje

  • Place of publication

    Poznań

  • Event location

    Poznań

  • Event date

    Jan 1, 2019

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article