So-Called Non-Subsective Adjectives
By Ellie Pavlick, Chris Callison-Burch. 2016
16 citations recorded by the source corpus.
The interpretation of adjective-noun pairs plays a crucial role in tasks such as recognizing textual entailment. Formal semantics often places adjectives into a taxonomy which should dictate adjectives’ entailment behavior when placed in adjective-noun compounds. However, we show experimentally that the behavior of subsective adjectives (e.g. red ) ver-sus non-subsective adjectives (e.g. fake ) is not as cut and dry as often assumed. For example, inferences are not always symmetric: while ID is generally considered to be mutually exclu-sive with fake ID , fake ID is considered to entail ID . We discuss the implications of these findings for automated natural language understanding.
Subfields: Artificial Intelligence, Language and Linguistics, Computational Linguistics & Semantics, Linguistics, Philosophy
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In Artificial Intelligence
- Tom Kwiatkowski
- Ellie Pavlick
- Samuel R. Bowman
- Luke S. Zettlemoyer
- Percy Liang
- Yonatan Belinkov
- Mohit Bansal
- Hannaneh Hajishirzi
In Computational Linguistics & Semantics
In Linguistics
In Philosophy
Citations in the corpus
- Inherent Disagreements in Human Textual Inferences (2019, background): “…(Poesio and Artstein, 2005; Versley, 2008; Simons et al., 2010; Recasens et al., 2011; de Marneffe et al., 2012; Passonneau et al., 2012; Pavlick and Callison-Burch, 2016a,b; Tonhauser et al., 2018, among others) suggesting computational models would benefit from focusing on ‘‘speaker…”