Graded and Word-Sense-Disambiguation Decisions in Corpus Pattern Analysis: a Pilot Study

LREC 2016  ·  Silvie Cinkov{\'a}, Ema Krej{\v{c}}ov{\'a}, Anna Vernerov{\'a}, V{\'\i}t Baisa ·

We present a pilot analysis of a new linguistic resource, VPS-GradeUp (available at http://hdl.handle.net/11234/1-1585). The resource contains 11,400 graded human decisions on usage patterns of 29 English lexical verbs, randomly selected from the Pattern Dictionary of English Verbs (Hanks, 2000 2014) based on their frequency and the number of senses their lemmas have in PDEV. This data set has been created to observe the interannotator agreement on PDEV patterns produced using the Corpus Pattern Analysis (Hanks, 2013). Apart from the graded decisions, the data set also contains traditional Word-Sense-Disambiguation (WSD) labels. We analyze the associations between the graded annotation and WSD annotation. The results of the respective annotations do not correlate with the size of the usage pattern inventory for the respective verbs lemmas, which makes the data set worth further linguistic analysis.

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