Name
Abstract | ||
|---|---|---|
We present a simple, two-steps supervised strategy for the identification and classification of thematic roles in natural language texts. We employ no external source of information but automatic parse trees of the input sentences. We use a few attribute-value features and tree kernel functions applied to specialized structured features. The resulting system has an F1 of 75.44 on the SemEval2007 closed task on semantic role labeling. |
Year | Venue | Keywords |
|---|---|---|
2007 | SemEval@ACL | resulting system,input sentence,specialized structured feature,thematic role,thematic role classification,external source,automatic parse tree,tree kernel,attribute-value feature,natural language text,semantic role,semeval2007 closed task,kernel function,natural language |
Field | DocType | Citations |
Computer science,Tree kernel,Natural language,Artificial intelligence,Natural language processing,Thematic map,Parsing,Semantic role labeling | Conference | 1 |
PageRank | References | Authors |
0.35 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| daniele pighin | 1 | 289 | 18.72 |
| Alessandro Moschitti | 2 | 3262 | 177.68 |
| Roberto Basili | 3 | 1308 | 155.68 |