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|a Hervaś, Raquel
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|a Finlayson, Mark Alan
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|a The prevalence of descriptive referring expressions in news and narrative
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|b © Association for Computational Linguistics,
|c 2022-04-06T17:21:36Z.
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|u https://hdl.handle.net/1721.1/141720
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|a Generating referring expressions is a key step in Natural Language Generation. Researchers have focused almost exclusively on generating distinctive referring expressions, that is, referring expressions that uniquely identify their intended referent. While undoubtedly one of their most important functions, referring expressions can be more than distinctive. In particular, descriptive referring expressions - those that provide additional information not required for distinction - are critical to flu- ent, efficient, well-written text. We present a corpus analysis in which approximately one-fifth of 7,207 referring expressions in 24,422 words of news and narrative are descriptive. These data show that if we are ever to fully master natural language generation, especially for the genres of news and narrative, researchers will need to de- vote more attention to understanding how to generate descriptive, and not just distinctive, referring expressions.
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|a This material is based on work supported by the U.S. Office of Naval Research, Grant No. N00014-09-1-0597. Any opinions, findings, conclusions or recommendations therein are those of the author(s) and do not necessarily reflect the views of the Office of Naval Research.
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