Co reference resolution
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Co-reference resolution..Pronominal resolution using Hobb's algorithm

Co-reference resolution..Pronominal resolution using Hobb's algorithm

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    Co reference resolution Co reference resolution Presentation Transcript

    • Coreference Resolution USING HOBBS‟S ALGORITHM Hemant Kumar (10579) Babul Bhanu (10545) Pratheek Adidela (10583) Shekhar Kumar (09562)
    • Contents  What is coreference resolution  Anaphoric and Cataphoric references  Direct and indirect anaphora  Hobbs‟s algorithm  Hobb‟s algorithm for Hindi  Problems in implementation  Applications
    • What is Coreference Resolution  In computational linguistics, Coreference resolution is a well-studied problem in discourse. To derive the correct interpretation of text, or even to estimate the relative importance of various mentioned subjects, pronouns and other referring expressions must be connected to the right individuals.  There are two types of references: When the reader must look back to the previous context, Coreference is called anaphoric reference. When the reader must look forward, it is cataphoric reference.
    • Anaphoric and Cataphoric references  Cataphora In linguistics, cataphora is used to first insert an expression or word that co-refers with a later expression in the discourse. An example of strict, sentence-internal cataphora in English is the following sentence “When he arrived home, John went to sleep.”  Anaphora In linguistics, anaphora is the use of an expression the interpretation of which depends upon another expression in context (its antecedent or postcedent).In the sentence “Sally arrived, but nobody saw her” the pronoun „her‟ is anaphoric, referring back to Sally.
    • Hobbs‟s algorithm  Hobbs‟s algorithm is mainly focused on “surface parse tree”. By this is means that the tree that exhibits the grammatical structure of the sentences (its division into subject, verb, objects, adverbials, etc.) without permuting or omitting any of the words in a sentence.  The naïve algorithm traverses the surface parse tree in a particular order looking for a noun phrase of the correct gender and number.
    • Hobbs‟s algorithm for Hindi  Pronouns in Hindi exhibit a great deal of ambiguity.  Pronouns in the first, second and third person do not convey any information about the gender  Redefined the grammar for Hindi
    • EXAMPLE 1 Non-Reflexive pronoun S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss uske VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss uske VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss uske VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss uske VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss uske VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss uske VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • Previous sentence S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss uske VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 EXAMPLE 2 Reflexive pronoun VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss apne VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss apne VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss apne VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss apne VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss apne VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • S1 VP2 NP_erg(SUB) Nbar Noun Mr.Smith Postp ne NP2_acc(DO) Nbar Postp ko Noun Driver Pronoun_poss apne VP1 VP PP_loc NP1(PO) postp mein Nbar Noun truck Verb dekha
    • Challenges in implementation  Parts of speech tagger  Richness of word database  In Hindi the gender of noun is identified by using verbs
    • Applications  English – Hindi machine translation  Machine learning
    • THANK YOU