Using Semantic Overlap Scoring in Answering TREC Relationship Questions

Gregory Marton, Boris Katz


Abstract
A first step in answering complex questions, such as those in the “Relationship”' task of the Text REtrieval Conference's Question Answering track (TREC/QA), is finding passages likely to contain pieces of the answer---passage retrieval. We introduce semantic overlap scoring, a new passage retrieval algorithm that facilitates credit assignment for inexact matches between query and candidate answer. Our official submission ranked best among fully automatic systems, at 23% F-measure, while the best system, with manual input, reached 28%. We use our Nuggeteer tool to robustly evaluate each component of our Relationship system post hoc. Ablation studies show that semantic overlap scoring achieves significant performance improvements over a standard passage retrieval baseline.
Anthology ID:
L06-1493
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Editors:
Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/790_pdf.pdf
DOI:
Bibkey:
Cite (ACL):
Gregory Marton and Boris Katz. 2006. Using Semantic Overlap Scoring in Answering TREC Relationship Questions. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
Using Semantic Overlap Scoring in Answering TREC Relationship Questions (Marton & Katz, LREC 2006)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/790_pdf.pdf