@inproceedings{marton-katz-2006-using,
title = "Using Semantic Overlap Scoring in Answering {TREC} Relationship Questions",
author = "Marton, Gregory and
Katz, Boris",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Gangemi, Aldo and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Tapias, Daniel",
booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
month = may,
year = "2006",
address = "Genoa, Italy",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/790_pdf.pdf",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Using Semantic Overlap Scoring in Answering TREC Relationship Questions
%A Marton, Gregory
%A Katz, Boris
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Gangemi, Aldo
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Tapias, Daniel
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 May
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F marton-katz-2006-using
%X 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.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/790_pdf.pdf
Markdown (Informal)
[Using Semantic Overlap Scoring in Answering TREC Relationship Questions](http://www.lrec-conf.org/proceedings/lrec2006/pdf/790_pdf.pdf) (Marton & Katz, LREC 2006)
ACL