A System for Experiments with Dependency Parsers

Kiril Simov, Iliana Simova, Ginka Ivanova, Maria Mateva, Petya Osenova


Abstract
In this paper we present a system for experimenting with combinations of dependency parsers. The system supports initial training of different parsing models, creation of parsebank(s) with these models, and different strategies for the construction of ensemble models aimed at improving the output of the individual models by voting. The system employs two algorithms for construction of dependency trees from several parses of the same sentence and several ways for ranking of the arcs in the resulting trees. We have performed experiments with state-of-the-art dependency parsers including MaltParser, MSTParser, TurboParser, and MATEParser, on the data from the Bulgarian treebank -- BulTreeBank. Our best result from these experiments is slightly better then the best result reported in the literature for this language.
Anthology ID:
L14-1005
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)
Note:
Pages:
4061–4065
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1005_Paper.pdf
DOI:
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1005_Paper.pdf