Predicate Argument Structures for Information Extraction from Dependency Representations: Null Elements are Missing

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 515)

Abstract

State of the art parsers are currently trained on converted versions of Penn Treebank into dependency representations which however don’t include null elements. This is done to facilitate structural learning and prevent the probabilistic engine to postulate the existence of deprecated null elements everywhere (see [15]). However it is a fact that in this way, the semantics of the representation used and produced on runtime is inconsistent and will reduce dramatically its usefulness in real life applications like Information Extraction, Q/A and other semantically driven fields by hampering the mapping of a complete logical form. What systems have come up with are “Quasi”-logical forms or partial logical forms mapped directly from the surface representation in dependency structure. We show the most common problems derived from the conversion and then describe an algorithm that we have implemented to apply to our converted Italian Treebank, that can be used on any CONLL-style treebank or representation to produce an “almost complete” semantically consistent dependency treebank.

Keywords

Predicate argument structures Dependency structures  Null elements Logical form Information extraction for question answering and text understanding 

Notes

Acknowledgments

This work has been partially funded by the PARLI Project (Portale per l’Accesso alle Risorse Linguistiche per l’Italiano—MIUR—PRIN 2008).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Linguistic Studies and Comparative Cultures and Department of Computer scienceCa’ Foscari UniversityVeniceItaly

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