Name
Abstract | ||
|---|---|---|
In this paper, we present a database-supported corpus study where we combine automatically obtained linguistic information from a statistical dependency parser, namely the occurrence of a dative argument, with predictions from a theory on the argument structure of German particle verbs with nach. The theory predicts five readings of nach which behave differently with respect to dative licensing in their argument structure. From a huge German web corpus, we extracted sentences for a subset of nach-particle verbs for which no dative is expected by the theory. Making use of a relational database management system, we bring together the corpus sentences and the lemmas manually annotated along the lines of the theory. We validate the theoretical predictions against the syntactic structure of the corpus sentences, which we obtained from a statistical dependency parser. We find that, in principle, the theory is borne out by the data, however, manual error analysis reveals cases for which the theory needs to be extended. |
Year | Venue | Keywords |
|---|---|---|
2012 | LREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | German particle verbs,database,corpus study |
Field | DocType | Citations |
Rule-based machine translation,Computer science,Speech recognition,Dependency grammar,Semantic theory of truth,Artificial intelligence,Relational database management system,Natural language processing,Lemma (mathematics),German,Syntactic structure,Dative case | Conference | 1 |
PageRank | References | Authors |
0.44 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Boris Haselbach | 1 | 4 | 1.65 |
| wolfgang seeker | 2 | 121 | 10.56 |
| Kerstin Eckart | 3 | 49 | 7.77 |