TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Schüller, Peter
T1  - MoSTNER: Morphology-aware Split-Tag German NER with Factorie
N2  - MoSTNER is a German NER system based on machine learning with log-linear models and morphology-aware features. We use morphological analysis with Morphisto for generating features, moreover we use German Wikipedia as a gazetteer and perform punctuation-aware and morphology-aware page title matching. We use four types of factor graphs where NER labels are single variables or split into prefix (BILOU) and type (PER, LOC, etc.) variables. Our system supports nested NER (two levels), for training we use SampleRank, for prediction Iterated Conditional Modes, the implementation is based on Python and Factorie.
KW  - Computerlinguistik
KW  - NER
KW  - Named entity recognition
Y1  - 2014
U6  - https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-3030
UN  - https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-3030
SN  - 978-3-934105-47-8
SB  - 978-3-934105-47-8
ER  -