Facing the Identification Problem in Language-Related Scientific Data Analysis.

Joseph Mariani, Christopher Cieri, Gil Francopoulo, Patrick Paroubek, Marine Delaborde


Abstract
This paper describes the problems that must be addressed when studying large amounts of data over time which require entity normalization applied not to the usual genres of news or political speech, but to the genre of academic discourse about language resources, technologies and sciences. It reports on the normalization processes that had to be applied to produce data usable for computing statistics in three past studies on the LRE Map, the ISCA Archive and the LDC Bibliography. It shows the need for human expertise during normalization and the necessity to adapt the work to the study objectives. It investigates possible improvements for reducing the workload necessary to produce comparable results. Through this paper, we show the necessity to define and agree on international persistent and unique identifiers.
Anthology ID:
L14-1717
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
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Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/945_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Joseph Mariani, Christopher Cieri, Gil Francopoulo, Patrick Paroubek, and Marine Delaborde. 2014. Facing the Identification Problem in Language-Related Scientific Data Analysis.. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Facing the Identification Problem in Language-Related Scientific Data Analysis. (Mariani et al., LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/945_Paper.pdf