Transition-based combinatory categorial grammar parsing for English and Hindi
Given a natural language sentence, parsing is the task of assigning it a grammatical structure, according to the rules within a particular grammar formalism. Different grammar formalisms like Dependency Grammar, Phrase Structure Grammar, Combinatory Categorial Grammar, Tree Adjoining Grammar are explored in the literature for parsing. For example, given a sentence like âJohn ate an appleâ, parsers based on the widely used dependency grammars find grammatical relations, such as that âJohnâ is the subject and âappleâ is the object of the action âateâ. We mainly focus on Combinatory Categorial Grammar (CCG) in this thesis. In this thesis, we present an incremental algorithm for parsing CCG for two diverse languages: English and Hindi. English is a fixed word order, SVO (Subject-Verb- Object), and morphologically simple language, whereas, Hindi, though predominantly a SOV (Subject-Object-Verb) language, is a free word order and morphologically rich language. Developing an incremental parser for Hindi is really challenging since the predicate needed to resolve dependencies comes at the end. As previously available shift-reduce CCG parsers use English CCGbank derivations which are mostly right branching
Ambati, Bharat Ram
CCG ; combinatory categorial grammar ; transition-based ; parses
Transition-based combinatory categorial grammar parsing for English and Hindi. Given a natural language sentence, parsing is the task of assigning it a grammatical structure, according to the rules within a particular grammar formalism. Different grammar formalisms like Dependency Grammar, Phrase Structure Grammar, Combinatory Categorial Grammar, Tree Adjoining Grammar are explored in the literature for parsing. For example, given a sentence like âJohn ate an appleâ, parsers based on the widely used dependency grammars find grammatical relations, such as that âJohnâ is the subject and âappleâ is the object of the action âateâ. We mainly focus on Combinatory Categorial Grammar (CCG) in this thesis. In this thesis, we present an incremental algorithm for parsing CCG for two diverse languages: English and Hindi. English is a fixed word order, SVO (Subject-Verb- Object), and morphologically simple language, whereas, Hindi, though predominantly a SOV (Subject-Object-Verb) language, is a free word order and morphologically rich language. Developing an incremental parser for Hindi is really challenging since the predicate needed to resolve dependencies comes at the end. As previously available shift-reduce CCG parsers use English CCGbank derivations which are mostly right branching
transition based combinatory_categorial grammar parse english given natural_language sentence parse task assign grammatical_structure accord rule within particular grammar formalism different grammar formalism like dependency_grammar phrase_structure_grammar categorial_grammar tree grammar explore literature parsing example give sentence like john parser base widely_use dependency_grammar grammatical_relation john subject object action mainly_focus categorial_grammar ccg thesis present incremental algorithm parse ccg diverse language english english fix word_order svo subject verb object morphologically simple language whereas though predominantly subject_object verb language free_word order morphologically rich language developing incremental parser really challenge since predicate need resolve dependency come end previously available shift reduce ccg parser use english derivation mostly right