Paraphrase and Textual Entailment Generation

Varování

Publikace nespadá pod Filozofickou fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.

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NEVĚŘILOVÁ Zuzana

Rok publikování 2014
Druh Článek ve sborníku
Konference Proceedings of 17th International Conference on Text, Speech, and Dialogue, TSD 2014
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
Doi http://dx.doi.org/10.1007/978-3-319-10816-2_36
Obor Informatika
Klíčová slova textual entailment; paraphrase; natural language generation
Přiložené soubory
Popis One particular information can be conveyed by many different sentences. This variety concerns the choice of vocabulary and style as well as the level of detail (from laconism or succinctness to total verbosity). Although verbosity in written texts is considered bad style, generated verbosity can help natural language processing (NLP) systems to fill in the implicit knowledge. The paper presents a rule-based system for paraphrasing and textual entailment generation in Czech. The inner representation of the input text is transformed syntactically or lexically in order to produce two type of new sentences: paraphrases (sentences with similar meaning) and entailments (sentences that humans will infer from the input text). The transformations make use of several language resources as well as a natural language generation (NLG) subsystem. The paraphrases and entailments are annotated by one or more annotators. So far, we annotated 3,321 paraphrases and textual entailments, from which 1,563 were judged correct (47.1 %), 1,238 (37.3 %) were judged incorrect entailments, and 520 (15.6 %) were judged non-sense. Paraphrasing and textual entailment can be put into effect in chatbots, text summarization or question answering systems. The results can encourage application-driven creation of new language resources or improvement of the current ones.
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