Name
Abstract | ||
|---|---|---|
Recognizing Textual Entailment (RTE) is a task in which two text fragments are processed by system to determine whether the meaning of hypothesis is entailed from another text or not. Although a considerable number of studies have been made on recognizing textual entailment, little is known about the power of linguistic phenomenon for recognizing inference in text. The objective of this paper is to provide a comprehensive analysis of identifying linguistic phenomena for recognizing inference in text (RITE). In this paper, we focus on RITE-VAL System Validation subtask and propose a model by using an analysis of identifying linguistic phenomena for Recognizing Inference in Text (RITE) using the development dataset of NTCIR-11 RITE-VAL subtask. The experimental results suggest that well identified linguistic phenomenon category could enhance the accuracy of textual entailment system. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/IRI.2014.7051945 | IRI |
Keywords | Field | DocType |
identifying linguistic phenomena analysis,inference mechanisms,recognizing textual entailment,ntcir-11 rite- val sub-task,machine learning,comprehensive analysis,knowledge-based,textual entailment,recognizing inference in text,natural language processing,text analysis,linguistic phenomena | Text graph,System validation,Rite,Textual entailment,Inference,Computer science,Natural language processing,Artificial intelligence,Phenomenon,Linguistics | Conference |
Citations | PageRank | References |
1 | 0.35 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min-Yuh Day | 1 | 198 | 29.24 |
| Ya-Jung Wang | 2 | 1 | 0.69 |