Konferenzbeitrag
A harmonised testsuite for POS tagging of German social media data
We present a testsuite for POS tagging German web data. Our testsuite provides the original raw text as well as the gold tokenisations and is annotated for parts-of-speech. The testsuite includes a new dataset for German tweets, with a current size of 3,940 tokens. To increase the size of the data, we harmonised the annotations in already existing web corpora, based on the Stuttgart-Tübingen Tag Set. The current version of the corpus has an overall size of 48,344 tokens of web data, around half of it from Twitter. We also present experiments, showing how different experimental setups (training set size, additional out-of-domain training data, self-training) influence the accuracy of the taggers. All resources and models will be made publicly available to the research community.
- Sprache
-
Englisch
- Thema
-
Korpus <Linguistik>
Deutsch
Soziale Software
Sprache
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Rehbein, Ines
Ruppenhofer, Josef
Zimmermann, Victor
- Ereignis
-
Veröffentlichung
- (wer)
-
Vienna, Austria : Austrian academy of sciences
- (wann)
-
2018-09-20
- URN
-
urn:nbn:de:bsz:mh39-79318
- Letzte Aktualisierung
-
06.03.2025, 09:00 MEZ
Datenpartner
Leibniz-Institut für Deutsche Sprache - Bibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Konferenzbeitrag
Beteiligte
- Rehbein, Ines
- Ruppenhofer, Josef
- Zimmermann, Victor
- Vienna, Austria : Austrian academy of sciences
Entstanden
- 2018-09-20
Ähnliche Objekte (12)
A New Resource for German Causal Language
Catching the common cause: extraction and annotation of causal relations and their participants
There’s no Data like More Data? Revisiting the Impact of Data Size on a Classification Task
Evaluating the Impact of Coder Errors on Active Learning
Yes we can!? Annotating the senses of English modal verbs
Semantic frames as an anchor representation for sentiment analysis
Detecting the boundaries of sentence-like units on spoken German
Who is we? Disambiguating the referents of first person plural pronouns in parliamentary debates
Improving Sentence Boundary Detection for Spoken Language Transcripts
Fine-grained Named Entity Annotations for German Biographic Interviews
MaJo - A Toolkit for Supervised Word Sense Disambiguation and Active Learning
Bringing Active Learning to Life
A New Resource for German Causal Language
Catching the common cause: extraction and annotation of causal relations and their participants
There’s no Data like More Data? Revisiting the Impact of Data Size on a Classification Task
Evaluating the Impact of Coder Errors on Active Learning
Yes we can!? Annotating the senses of English modal verbs
Semantic frames as an anchor representation for sentiment analysis
Detecting the boundaries of sentence-like units on spoken German
Who is we? Disambiguating the referents of first person plural pronouns in parliamentary debates
Improving Sentence Boundary Detection for Spoken Language Transcripts
Fine-grained Named Entity Annotations for German Biographic Interviews
MaJo - A Toolkit for Supervised Word Sense Disambiguation and Active Learning
Bringing Active Learning to Life
A New Resource for German Causal Language
Catching the common cause: extraction and annotation of causal relations and their participants
There’s no Data like More Data? Revisiting the Impact of Data Size on a Classification Task
Evaluating the Impact of Coder Errors on Active Learning
Yes we can!? Annotating the senses of English modal verbs
Semantic frames as an anchor representation for sentiment analysis
Detecting the boundaries of sentence-like units on spoken German
Who is we? Disambiguating the referents of first person plural pronouns in parliamentary debates
Improving Sentence Boundary Detection for Spoken Language Transcripts
Fine-grained Named Entity Annotations for German Biographic Interviews
MaJo - A Toolkit for Supervised Word Sense Disambiguation and Active Learning