Browsing by Author "Romeo, Lauren"

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  • Romeo, Lauren; Mendes, Sara; Bel Rafecas, Núria (ACL (Association for Computational Linguistics), 2014)
    The work detailed in this paper describes a 2-step cascade approach for the classification of complex-type nominals. We describe an experiment that demonstrates how a cascade approach performs when the task consists in ...
  • Bel Rafecas, Núria; Romeo, Lauren; Padró, Muntsa (ELRA (European Language Resources Association), 2012)
    The work we present here addresses cue-based noun classification in English and Spanish. Its main objective is to automatically acquire lexical semantic information by classifying nouns into previously known noun lexical ...
  • Romeo, Lauren; Lebani, Gianluca E.; Bel Rafecas, Núria; Lenci, Alessandro (ACL (Association for Computational Linguistics), 2014)
    This paper empirically evaluates the performances of different state-of-the-art distributional models in a nominal lexical semantic classification task. We consider models that exploit various types of distributional ...
  • Romeo, Lauren; Martínez Alonso, Héctor; Bel Rafecas, Núria (ACL (Association for Computational Linguistics), 2013)
    This paper describes an effort to capture the sense alternation of dot-type nominals using Word Sense Induction (WSI). We propose dot-type nominals generate more semantically consistent groupings when clustered into more ...
  • Hernández Leo, Davinia; Romeo, Lauren; Carralero, Miguel A.; Chacón Pérez, Jonathan, 1986-; Carrió, Mar; Moreno, Pau; Blat, Josep (Elsevier, 2011)
    Two important challenges that teachers are currently facing are the sharing and the collaborative authoring of their learning design solutions, such as didactical units and learning materials. On the one hand, there are ...
  • Romeo, Lauren; Mendes, Sara; Bel Rafecas, Núria (ACL (Association for Computational Linguistics), 2013)
    The work presented here depicts experiments toward the automatic classification of complex-type nominals using distributional information. We conducted two experiments: classifying complex-type nominals as members of ...
  • Romeo, Lauren; Mendes, Sara; Bel Rafecas, Núria (ACL (Association for Computational Linguistics), 2012)
    Acquiring lexical information is a complex problem, typically approached by relying on a number of contexts to contribute information for classification. One of the first issues to address in this domain is the determination ...
  • Romeo, Lauren; Mendes, Sara; Bel Rafecas, Núria (Association for Computational Linguistics (ACL), 2014)
    The work presented here addresses the use of unmarked contexts in pattern-based nominal lexical semantic classification. We define unmarked contexts to be the counterposition of the class-indicatory, or marked, contexts. ...

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