Konferenzbeitrag
POS error detection in automatically annotated corpora
Recent work on error detection has shown that the quality of manually annotated corpora can be substantially improved by applying consistency checks to the data and automatically identifying incorrectly labelled instances. These methods, however, can not be used for automatically annotated corpora where errors are systematic and cannot easily be identified by looking at the variance in the data. This paper targets the detection of POS errors in automatically annotated corpora, so-called silver standards, showing that by combining different measures sensitive to annotation quality we can identify a large part of the errors and obtain a substantial increase in accuracy.
- Language
-
Englisch
- Subject
-
Korpus <Linguistik>
Automatische Sprachanalyse
Annotation
Sprache
- Event
-
Geistige Schöpfung
- (who)
-
Rehbein, Ines
- Event
-
Veröffentlichung
- (who)
-
Stroudsburg, PA : ACL
- (when)
-
2016-11-21
- URN
-
urn:nbn:de:bsz:mh39-55986
- Last update
-
06.03.2025, 9:00 AM CET
Data provider
This object is provided by:
Leibniz-Institut für Deutsche Sprache - Bibliothek. If you have any questions about the object, please contact the 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
- Rehbein, Ines
- Stroudsburg, PA : ACL
Time of origin
- 2016-11-21
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