Relational feature engineering of natural language processing

Authors:
Hamidreza Kobdani;Hinrich Schütze;Andre Burkovski;Wiltrud Kessler;Gunther Heidemann
Affiliations:
Stuttgart University, Stuttgart, Germany;Stuttgart University, Stuttgart, Germany;Stuttgart University, Stuttgart, Germany;Stuttgart University, Stuttgart, Germany;Stuttgart University, Stuttgart, Germany
Venue:
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Year:
2010

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Abstract

We present a new framework for feature engineering of natural language processing that is based on a relational data model of text. It includes fast and flexible methods for implementing and extracting new features and thereby reduces the effort of creating an NLP system for a particular task. In an instantiation and evaluation of the framework for the problem of coreference resolution in multiple languages, we were able to obtain competitive results in a short implementation period. This demonstrates the potential power of our framework for feature engineering.