Textual Entailment Recognition (TET) Task

From GM-RKB
Jump to navigation Jump to search

A Textual Entailment Recognition (TET) Task is a linguistic expression entailment recognition task (that recognizes whether a hypothesis) within a given text item [math]\displaystyle{ h }[/math] is entailed by some other text item [math]\displaystyle{ t }[/math].



References

2013

2011

  • http://www.nist.gov/tac/2011/RTE/
    • Given two text fragments called 'Text' and 'Hypothesis', Textual Entailment Recognition is the task of determining whether the meaning of the Hypothesis is entailed (can be inferred) from the Text. The goal of the first RTE Challenge was to provide the NLP community with a benchmark to test progress in recognizing textual entailment, and to compare the achievements of different groups. Since its inception in 2004, the RTE Challenges have promoted research in textual entailment recognition as a generic task that captures major semantic inference needs across many natural language processing applications, such as Question Answering (QA), Information Retrieval (IR), Information Extraction (IE), and multi-document Summarization.

2007

2006