Name
Abstract | ||
|---|---|---|
In this article, we underpin the intuition that frame semantic information is a useful resource for modelling textual entailment. To this end, we provide a manual frame semantic annotation for the test set used in the second recognizing textual entailment (RTE) challenge – the FrameNet-annotated textual entailment (FATE) corpus – and discuss experiments we conducted on this basis. In particular, our experiments show that the frame semantic lexicon provided by the Berkeley FrameNet project provides surprisingly good coverage for the task at hand. We identify issues of automatic semantic analysis components, as well as insufficient modelling of the information provided by frame semantic analysis as reasons for ambivalent results of current systems based on frame semantics. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1017/S1351324909990131 | Natural Language Engineering |
Keywords | Field | DocType |
framenet-annotated textual entailment,frame semantic analysis,automatic semantic analysis component,frame semantic information,manual frame semantic annotation,textual entailment,frame semantics,berkeley framenet project,insufficient modelling,frame semantic lexicon | Data mining,Textual entailment,Semantic annotation,Computer science,Intuition,Semantic information,Artificial intelligence,Frame semantics,Natural language processing,Semantic lexicon,FrameNet,Test set | Journal |
Volume | Issue | ISSN |
15 | 4 | 1351-3249 |
Citations | PageRank | References |
28 | 1.18 | 20 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aljoscha Burchardt | 1 | 188 | 18.51 |
| Marco Pennacchiotti | 2 | 1742 | 84.81 |
| Stefan Thater | 3 | 756 | 38.54 |
| Manfred Pinkal | 4 | 1116 | 69.77 |