Answer Validation through Textual Entailment

  • Partha Pakray
Conference paper

DOI: 10.1007/978-3-642-22327-3_48

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6716)
Cite this paper as:
Pakray P. (2011) Answer Validation through Textual Entailment. In: Muñoz R., Montoyo A., Métais E. (eds) Natural Language Processing and Information Systems. NLDB 2011. Lecture Notes in Computer Science, vol 6716. Springer, Berlin, Heidelberg


Ongoing research work on an Answer Validation System (AV) based on Textual Entailment and Question Answering has been presented. A number of answer validation modules have been developed based on Textual Entailment, Named Entity Recognition, Question-Answer type analysis, Chunk boundary module and Syntactic similarity module. These answer validation modules have been integrated using a voting technique. We combine the question and the answer into the Hypothesis (H) and the Supporting Text as Text (T) to identify the entailment relation as either “VALIDATED” or “REJECTED”. The important features in the lexical Textual Entailment module are: WordNet based unigram match, bi-gram match and skip-gram. In the syntactic similarity module, the important features used are: subject-subject comparison, subject-verb comparison, object-verb comparison and cross subject-verb comparison. The precision, recall and f-score of the integrated AV system on the AVE 2008 English annotated test set have been observed as 0.66, 0.65 and 0.65 respectively that outperforms the best performing system at AVE 2008 in terms of f-score.


Answer Validation Exercise (AVE) Textual Entailment (TE) Named Entity (NE) Chunk Boundary Syntactic Similarity Question Type 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Partha Pakray
    • 1
  1. 1.Computer Science and Engineering DepartmentJadavpur UniversityKolkataIndia

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