Defining and Classifying Space Builders for Information Extraction

The paper addresses the question of Information Extraction aimed at multilingual text generation, or text re-writing. This method provides an alternative to traditional Machine Translation, but is also related to text summarization. Given a source text, a re-writing system selects and structures the textual information in order to generate a “content report”. The present approach is inspired by recent IE-research, classical speech act theory, and Cognitive Semantics, especially the Theory of Mental Spaces and employed in an experimental system for understanding of news reports. The authors focus on the problem of identification and interpretation of ‘space builders’, i.e. linguistic signals for establishing mental spaces.

• Publication year

  2018

• Venue

  NLUCS

• Publication date

  2018-08-31

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.5220/0002667500150028
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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