TY  - CHAP
U1  - Buchbeitrag
A1  - Fürbacher, Monica
A1  - Schneider, Roman
ED  - Calzolari, Nicoletta
ED  - Choukri, Khalid
ED  - Cieri, Christopher
ED  - Declerck, Thierry
ED  - Goggi, Sara
ED  - Hasida, Koiti
ED  - Isahara, Hitoshi
ED  - Maegaard, Bente
ED  - Mariani, Joseph
ED  - Mazo, Hélène
ED  - Moreno, Asuncion
ED  - Odijk, Jan
ED  - Piperidis, Stelios
ED  - Tokunaga, Takenobu
T1  - GeCoTagger: annotation of German verb complements with conditional random fields
T2  - Proceedings of the eleventh international conference on language resources and evaluation (LREC 2018), 7-12 May 2018, Miyazaki, Japan
N2  - Complement phrases are essential for constructing well-formed sentences in German. Identifying verb complements and categorizing complement classes is challenging even for linguists who are specialized in the field of verb valency. Against this background, we introduce an ML-based algorithm which is able to identify and classify complement phrases of any German verb in any written sentence context. We use a large training set consisting of example sentences from a valency dictionary, enriched with POS tagging, and the ML-based technique of Conditional Random Fields (CRF) to generate the classification models.
KW  - grammar and syntax
KW  - verb valency
KW  - machine learning methods
KW  - Grammatik
KW  - Deutsch
KW  - Ergänzung <Linguistik>
KW  - Verb
KW  - Valenz <Linguistik>
Y1  - 2018
U6  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-74887
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-74887
UR  - http://www.lrec-conf.org/proceedings/lrec2018/summaries/73.html
SN  - 979-10-95546-00-9
SB  - 979-10-95546-00-9
SP  - 2169
EP  - 2174
PB  - European language resources association (ELRA)
CY  - Paris, France
ER  -