Textual Entailment Recognition (TET) Task

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].

Context:
- Input:
  - a Hypothesis h
  - a Text Item t
  - optional: a Corpus that can act as Context or from which all entailments must be recognized.
- output:
  - All Sentences [math]\displaystyle{ S }[/math] from [math]\displaystyle{ C }[/math] that Entail h
- Performance Measure: human [math]\displaystyle{ h }[/math] reading [math]\displaystyle{ t }[/math] will infer that [math]\displaystyle{ h }[/math] is (most likely) True.
- It can be solved by a Textual Entailment Recognition System (that implements a Textual Entailment Recognition Algorithm.
Example(s):
- a PASCAL Textual Entailment Recognition Task.
- a TAC RTE Task.
- …
Counter-Example(s):
- a Question Answering Task.
- a Semantic Role Labeling Task.
- a Paraphrasing Task.
- a String Comparison Task.
- a Textual Inference Task.
See: Spoken Entailment Task, Textual Paraphrasing Task, Semantic Inference.

References

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.

http://pascallin.ecs.soton.ac.uk/Challenges/RTE/
(Burchardt et al., 2007) ⇒ Aljoscha Burchardt, Nils Reiter, Stefan Thater, and Anette Frank. (2007). “A Semantic Approach To Textual Entailment: System Evaluation and Task Analysis.” In: Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing table of contents
http://www.cs.biu.ac.il/~dagan/TE-Tutorial-ACL07.ppt
(Wang & Neumann, 2007) ⇒ R. Wang, and G. Neumann. (2007). “[Recognizing Textual Entailment Using a Subsequence Kernel Method].” In: Proceedings of AAAI Conference (AAAI 2007).
(Giuliano & Gliozzo, 2007) ⇒ Claudio Giuliano, and Alfio Gliozzo. (2007). “Instance based Lexical Entailment for Ontology Population.” In: Proceedings of ACL Conference (ACL 2007).