GLML: Annotating Argument Selection and Coercion

نویسندگان

  • James Pustejovsky
  • Jessica L. Moszkowicz
  • Olga Batiukova
  • Anna Rumshisky
چکیده

In this paper we introduce a methodology for annotating compositional operations in natural language text, and describe a mark-up language, GLML, based on Generative Lexicon, for identifying such relations. While most annotation systems capture surface relationships, GLML captures the “compositional history” of the argument selection relative to the predicate. We provide a brief overview of GL before moving on to our proposed methodology for annotating with GLML. There are three main tasks described in the paper: (i) Compositional mechanisms of argument selection; (ii) Qualia in modification constructions; (iii) Type selection in modification of dot objects. We explain what each task includes and provide a description of the annotation interface. We also include the XML format for GLML including examples of annotated sentences.

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تاریخ انتشار 2009