Towards deep content extraction from specialized discourse : the case of verbal relations in patent claims

Ferraro, Gabriela

Towards deep content extraction from specialized discourse : the case of verbal relations in patent claims

Document Type

Doctoral thesis
Published Version

Author

Ferraro, Gabriela

Director

Wanner, Leo

Publication Date

2012-07-20

Pages

159 p.

Citation

Ferraro, G. Towards deep content extraction from specialized discourse : the case of verbal relations in patent claims. Universitat Pompeu Fabra; 2012. handle: http://hdl.handle.net/10803/84174

This citation was generated automatically.

Doctoral program

Programa de doctorat en Tecnologies de la Informació i les Comunicacions

Abstract

This thesis addresses the problem of the development of Natural Language Processing techniques for the extraction and generalization of compositional and functional relations from specialized written texts and, in particular, from patent claims. One of the most demanding tasks tackled in the thesis is, according to the state of the art, the semantic generalization of linguistic denominations of relations between object components and processes described in the texts. These denominations are usually verbal expressions or nominalizations that are too concrete to be used as standard labels in knowledge representation forms -as, for example, “A leads to B”, and “C provokes D”, where “leads to” and “provokes” both express, in abstract terms, a cause, such that in both cases “A CAUSE B” and “C CAUSE D” would be more appropriate. A semantic generalization of the relations allows us to achieve a higher degree of abstraction of the relationships between objects and processes described in the claims and reduces their number to a limited set that is oriented towards relations as commonly used in the generic field of knowledge representation.
Esta tesis se centra en el del desarrollo de tecnologías del Procesamiento del Lenguage Natural para la extracción y generalización de relaciones encontradas en textos especializados; concretamente en las reivindicaciones de patentes. Una de las tareas más demandadas de nuestro trabajo, desde el punto vista del estado de la cuestión, es la generalización de las denominaciones lingüísticas de las relaciones. Estas denominaciones, usualmente verbos, son demasiado concretas para ser usadas como etiquetas de relaciones en el contexto de la representación del conocimiento; por ejemplo, “A lleva a B”, “B es el resultado de A” están mejor representadas por “A causa B”. La generalización de relaciones permite reducir el n\'umero de relaciones a un conjunto limitado, orientado al tipo de relaciones utilizadas en el campo de la representación del conocimiento.

Keywords

Artificial intelligence, Natural language processing, Relation extraction, Linguistic dependency, Deep syntactic parsing, Surface syntactic parsing, Valency structure, Relation generalization, Relation clustering, Relation cluster labeling, Text simplification, Patent processing, Patent claim processing, Meaning-Text Theory, Machine learning