Summary of the paper

Title Pattern-Based Extraction of Negative Polarity Items from Dependency-Parsed Text
Authors Fabienne Fritzinger, Frank Richter and Marion Weller
Abstract We describe a new method for extracting Negative Polarity Item candidates (NPI candidates) from dependency-parsed German text corpora. Semi-automatic extraction of NPIs is a challenging task since NPIs do not have uniform categorical or other syntactic properties that could be used for detecting them; they occur as single words or as multi-word expressions of almost any syntactic category. Their defining property is of a semantic nature, they may only occur in the scope of negation and related semantic operators. In contrast to an earlier approach to NPI extraction from corpora, we specifically target multi-word expressions. Besides applying statistical methods to measure the co-occurrence of our candidate expressions with negative contexts, we also apply linguistic criteria in an attempt to determine to which degree they are idiomatic. Our method is evaluated by comparing the set of NPIs we found with the most comprehensive electronic list of German NPIs, which currently contains 165 entries. Our method retrieved 142 NPIs, 114 of which are new.
Topics MultiWord Expressions & Collocations, Lexicon, lexical database, Semantics
Full paper Pattern-Based Extraction of Negative Polarity Items from Dependency-Parsed Text
Slides Pattern-Based Extraction of Negative Polarity Items from Dependency-Parsed Text
Bibtex @InProceedings{FRITZINGER10.267,
  author = {Fabienne Fritzinger and Frank Richter and Marion Weller},
  title = {Pattern-Based Extraction of Negative Polarity Items from Dependency-Parsed Text},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
 }
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