Summary of the paper

Title Computational Models for Event Type Classification in Context
Authors Alessandra Zarcone and Alessandro Lenci
Abstract Verb lexical semantic properties are only one of the factors that contribute to the determination of the event type expressed by a sentence, which is instead the result of a complex interplay between the verb meaning and its linguistic context. We report on two computational models for the automatic identification of event type in Italian. Both models use linguistically-motivated features extracted from Italian corpora. The main goal of our experiments is to evaluate the contribution of different types of linguistic indicators to identify the event type of a sentence, as well as to model various cases of context-driven event type shift. In the first model, event type identification has been modelled as a supervised classification task, performed with Maximum Entropy classifiers. In the second model, Self-Organizing Maps have been used to define and identify event types in an unsupervised way. The interaction of various contextual factors in determining the event type expressed by a sentence makes event type identification a highly challenging task. Computational models can help us to shed new light on the real structure of event type classes as well as to gain a better understanding of context-driven semantic shifts.
Topics Semantics, Acquisition, Machine Learning, Word Sense Disambiguation
Full paper Computational Models for Event Type Classification in Context
Slides -
Bibtex @InProceedings{ZARCONE08.315,
  author = {Alessandra Zarcone and Alessandro Lenci},
  title = {Computational Models for Event Type Classification in Context},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  month = {may},
  date = {28-30},
  address = {Marrakech, Morocco},
  editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-4-0},
  note = {},
  language = {english}

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