Empirical studies in learning to read

Authors:
Marjorie Freedman;Edward Loper;Elizabeth Boschee;Ralph Weischedel
Affiliations:
BBN Raytheon Technologies, Cambridge, MA;BBN Raytheon Technologies, Cambridge, MA;BBN Raytheon Technologies, Cambridge, MA;BBN Raytheon Technologies, Cambridge, MA
Venue:
FAM-LbR '10 Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading
Year:
2010

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Abstract

In this paper, we present empirical results on the challenge of learning to read. That is, given a handful of examples of the concepts and relations in an ontology and a large corpus, the system should learn to map from text to the concepts/relations of the ontology. In this paper, we report contrastive experiments on the recall, precision, and F-measure (F) of the mapping in the following conditions: (1) employing word-based patterns, employing semantic structure, and combining the two; and (2) fully automatic learning versus allowing minimal questions of a human informant.