Who mentions whom? Recognizing political actors in proceedings

Lennart Kerkvliet, Jaap Kamps, Maarten Marx


Abstract
We show that it is straightforward to train a state of the art named entity tagger (spaCy) to recognize political actors in Dutch parliamentary proceedings with high accuracy. The tagger was trained on 3.4K manually labeled examples, which were created in a modest 2.5 days work. This resource is made available on github. Besides proper nouns of persons and political parties, the tagger can recognize quite complex definite descriptions referring to cabinet ministers, ministries, and parliamentary committees. We also provide a demo search engine which employs the tagged entities in its SERP and result summaries.
Anthology ID:
2020.parlaclarin-1.7
Volume:
Proceedings of the Second ParlaCLARIN Workshop
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
LREC | ParlaCLARIN | WS
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
35–39
URL:
https://www.aclweb.org/anthology/2020.parlaclarin-1.7
DOI:
Bib Export formats:
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PDF:
https://www.aclweb.org/anthology/2020.parlaclarin-1.7.pdf

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