Konferenzbeitrag
Growing trees from morphs: Towards data-driven morphological parsing
We present a quantitative approach to disambiguating flat morphological analyses and producing more deeply structured analyses. Based on existing morphological segmentations, possible combinations of resulting word trees for the next level are filtered first by criteria of linguistic plausibility and then by weighting procedures based on the geometric mean. The frequencies for weighting are derived from three different sources (counts of morphs in a lexicon, counts of largest constituents in a lexicon, counts of token frequencies in a corpus) and can be used either to find the best analysis on the level of morphs or on the next higher constituent level. The evaluation shows that for this task corpus-based frequency counts are slightly superior to counts of lexical data.
- Language
-
Englisch
- Subject
-
Morphemanalyse
Segmentierung
Worthäufigkeit
Computerlinguistik
Deutsch
Linguistik
- Event
-
Geistige Schöpfung
- (who)
-
Steiner, Petra
Ruppenhofer, Josef
- Event
-
Veröffentlichung
- (who)
-
Gesellschaft für Sprachtechnologie and Computerlinguistik
- (when)
-
2016-09-01
- URN
-
urn:nbn:de:bsz:mh39-52323
- Last update
-
06.03.2025, 9:00 AM CET
Data provider
Leibniz-Institut für Deutsche Sprache - Bibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Konferenzbeitrag
Associated
- Steiner, Petra
- Ruppenhofer, Josef
- Gesellschaft für Sprachtechnologie and Computerlinguistik
Time of origin
- 2016-09-01
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