Name
Abstract | ||
|---|---|---|
In this paper we present the use of the AORTE system in recognizing textual entailment. AORTE allows the automatic acquisition and alignment of ontologies from text. The information resulted from aligning ontologies created from text fragments is used in classifying textual entailment. We further introduce the set of features used in classifying textual entailment. At the TAC RTE4 challenge the system evaluation yielded an accuracy of 68% on the two-way task, and 61% on the three way task using a simple decision tree classifier. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-00382-0_20 | CICLing |
Keywords | Field | DocType |
recognizing textual entailment,automatic acquisition,text fragment,tac rte4 challenge,simple decision tree classifier,aligning ontology,system evaluation,textual entailment,aorte system,two-way task,decision tree classifier | Ontology (information science),Ontology alignment,Pattern recognition,Textual entailment,Computer science,System evaluation,Natural language processing,Artificial intelligence,Decision tree learning | Conference |
Volume | ISSN | Citations |
5449 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Reda Siblini | 1 | 8 | 2.46 |
| Leila Kosseim | 2 | 313 | 43.58 |