Recognition Function

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A Recognition Function is a function structure that is a detection function and a classification function structure.




  • (Roth & Yih, 2002) ⇒ Dan Roth, and Wen-tau Yih. (2002). “Probabilistic Reasoning for Entity & Relation Recognition.” In: Proceedings of the 20th International Conference on Computational Linguistics (COLING 2002).
    • QUOTE: In all earlier works we know of, the tasks of identifying entities and relations were treated as separate problems. The common procedure is to first identify and classify entities using a named entity recognizer and only then determine the relations between the entities. However, this approach has several problems. First, errors made by the named entity recognizer propagate to the relation classifier and may degrade its performance significantly. For example, if “Boston” is mislabeled as a person, it will never be classified as the location of Poe’s birthplace. Second, relation information is sometimes crucial to resolving ambiguous named entity recognition. For instance, if the entity “JFK” is identified as the victim of the assassination, the named entity recognizer is unlikely to misclassify it as a location (e.g. JFK airport).



  • (Earley, 1970) ⇒ Jay Earley. (1970). “An Efficient Context-Free Parsing Algorithm.” In: Communications of the ACM, 13(2). doi:10.1145/362007.362035
    • QUOTE: A recognizer is an algorithm which takes as input a string and either accepts or rejects it depending on whether or not the string is a sentence of the grammar.