Name
Abstract | ||
|---|---|---|
We show that it is possible to learn the contexts for linguistic operations which map a semantic representation to a surface syntactic tree in sentence realization with high accuracy. We cast the problem of learning the contexts for the linguistic operations as classification tasks, and apply straightforward machine learning techniques, such as decision tree learning. The training data consist of linguistic features extracted from syntactic and semantic representations produced by a linguistic analysis system. The target features are extracted from links to surface syntax trees. Our evidence consists of four examples from the German sentence realization system code-named case assignment, assignment of verb position features, extraposition, and syntactic aggregation. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.3115/1073083.1073089 | ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics |
Keywords | Field | DocType |
german sentence realization system,machine-learned context,sentence realization,syntactic aggregation,surface syntactic tree,syntax tree,semantic representation,linguistic operation,decision tree learning,linguistic analysis system,case assignment,machine learning,data consistency,feature extraction,german | Extraposition,Deep linguistic processing,Computer science,Natural language processing,Artificial intelligence,Syntax,Verb,Linguistics,Sentence,Linguistic analysis,Machine learning,Decision tree learning,German | Conference |
Volume | Citations | PageRank |
P02-1 | 5 | 0.61 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Gamon | 1 | 1484 | 89.50 |
| Eric Ringger | 2 | 328 | 21.57 |
| Simon Corston-Oliver | 3 | 349 | 25.25 |
| Robert C. Moore | 4 | 2432 | 646.93 |