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Description
  • Language resources are hardly ever large enough. Building language resources that can be used as a gold standard for semantic analysis requires effort and investment. We present a prototype for acquiring language resources by means of a language game which is a cheap but long-term method. Games employed to acquire language resources are not new. For example games with a purpose are used for collecting common sense knowledge. The game presented in this paper is a work in progress. It collects annotated pairs text–hypothesis suitable for recognizing textual entailment in Czech. The game narrative is based on Sherlock Holmes and dr. Watson dialogues. For generating the dialogue line we use rule-based approaches such as syntactic analysis, anaphora resolution, synonym and hypernym replacement, word order rearrangement and verb frame based inference. To generate natural sounding sentences we added a language model score (based on n-gram frequencies in a corpus).
  • Language resources are hardly ever large enough. Building language resources that can be used as a gold standard for semantic analysis requires effort and investment. We present a prototype for acquiring language resources by means of a language game which is a cheap but long-term method. Games employed to acquire language resources are not new. For example games with a purpose are used for collecting common sense knowledge. The game presented in this paper is a work in progress. It collects annotated pairs text–hypothesis suitable for recognizing textual entailment in Czech. The game narrative is based on Sherlock Holmes and dr. Watson dialogues. For generating the dialogue line we use rule-based approaches such as syntactic analysis, anaphora resolution, synonym and hypernym replacement, word order rearrangement and verb frame based inference. To generate natural sounding sentences we added a language model score (based on n-gram frequencies in a corpus). (en)
Title
  • Acquiring Data for Textual Entailment Recognition
  • Acquiring Data for Textual Entailment Recognition (en)
skos:prefLabel
  • Acquiring Data for Textual Entailment Recognition
  • Acquiring Data for Textual Entailment Recognition (en)
skos:notation
  • RIV/00216224:14330/13:00070350!RIV14-MSM-14330___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • I, P(LM2010013), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 59365
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/13:00070350
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • extual entailment; language game; games with a purpose; GWAP (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [402A1E8D9A08]
http://linked.open...v/mistoKonaniAkce
  • Brno
http://linked.open...i/riv/mistoVydani
  • Brno
http://linked.open...i/riv/nazevZdroje
  • Seventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2013
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Nevěřilová, Zuzana
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Tribun EU
https://schema.org/isbn
  • 9788026305200
http://localhost/t...ganizacniJednotka
  • 14330
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