Summary of the paper

Title Graded and Word-Sense-Disambiguation Decisions in Corpus Pattern Analysis: a Pilot Study
Authors Silvie Cinkova, Ema Krejčová, Anna Vernerová and Vít Baisa
Abstract 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.
Topics Lexicon, Lexical Database, Corpus (Creation, Annotation, etc.), Word Sense Disambiguation
Full paper Graded and Word-Sense-Disambiguation Decisions in Corpus Pattern Analysis: a Pilot Study
Bibtex @InProceedings{CINKOVA16.506,
  author = {Silvie Cinkova and Ema Krejčová and Anna Vernerová and Vít Baisa},
  title = {Graded and Word-Sense-Disambiguation Decisions in Corpus Pattern Analysis: a Pilot Study},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portoro┼ż, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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