עיבוד שפות טבעיות - שיעור שבע Partial Parsing

עיבוד שפות טבעיות - שיעור שבעPartial Parsing אורן גליקמן המחלקה למדעי המחשב אוניברסיטת בר אילן 88-680

Syntax • The study of grammatical relations between words and other units within the sentence.The Concise Oxford Dictionary of Linguistics • the way in which linguistic elements (as words) are put together to form constituents (as phrases or clauses)Merriam-Webster Dictionary 88-680

Brackets • “I prefer a morning flight” • [S [NP [pro I]][VP [V prefer][NP [Det a] [Nom [N morning] [ N flight]]]]]] 88-680

Parse Tree S VP NP NP Nom Det Noun Noun Pronoun Verb I prefer a morning flight 88-680

Parsing • The problem of mapping from a string of words to to its parse tree is called parsing. 88-680

Generative Grammar • A set of rules which indicate precisely what can be and cannot be a sentence in a language. • A grammar which precisely specifies the membership of the set of all the grammatical sentences in the language in question and therefore excludes all the ungrammatical sentences. 88-680

Formal Languages • The set of all grammatical sentences in a given natural language. • Are natural languages regular? 88-680

English is not a regular language! • anbn is not regular • Look at the following English sentences: • John and Mary like to eat and sleep, respectively. • John, Mary, and Sue like to eat, sleep, and dance, respectively. • John, Mary, Sue, and Bob like to eat, sleep, dance, and cook, respectively. 88-680

Constituents • Certain groupings of words behave as constituents. • Constituents are able to occur in various sentence positions: • ראיתי את הילד הרזה • ראיתי אותו מדבר עם הילד הרזה • הילד הרזה גר ממול 88-680

The Noun Phrase (NP) • Examples: • He • Ariel Sharon • The prime minister • The minister of defense during the war in Lebanon. • They can all appear in a similar context:___ was born in Kfar-Malal 88-680

Prepositional Phrases • Examples: • the man in the white suit • Come and look at my paintings • Are you fond of animals? • Put that thing on the floor 88-680

Verb Phrases • Examples: • Getting to school on timewas a struggle. • Hewas trying to keep his temper. • That womanquickly showed me the way to hide. 88-680

Chunking • Text chunking is dividing sentences into non-overlapping phrases. • Noun phrase chunking deals with extracting the noun phrases from a sentence. • While NP chunking is much simpler than parsing, it is still a challenging task to build a accurate and very efficient NP chunker. 88-680

What is it good for • The importance of chunking derives from the fact that it is used in many applications: • Information Retrieval & Question Answering • Machine Translation • Preprocessing before full syntactic analysis • Text to speech • Many other Applications 88-680

What kind of structures should a partial parser identify? • Different structures useful for different tasks: • Partial constituent structure[NPI] [VPsaw [NPa tall man in the park]]. • Prosodic segments[I saw] [a tall man] [in the park]. • Content word groups[I] [saw] [a tall man] [in the park]. 88-680

Chunk Parsing • Goal: divide a sentence into a sequence of chunks. • Chunks are non-overlapping regions of a text: • [I] saw [a tall man] in [the park]. • Chunks are non-recursive • a chunk can not contain other chunks • Chunks are non-exhaustive • not all words are included in chunks 88-680

Chunk Parsing Examples • Noun-phrase chunking: • [I] saw [a tall man] in [the park]. • Verb-phrase chunking: • The man who [was in the park] [saw me]. • Prosodic chunking: • [I saw] [a tall man] [in the park]. 88-680

Chunks and Constituency Constituents: [a tall man in [the park]]. Chunks: [a tall man] in [the park]. • Chunks are not constituents • Constituents are recursive • Chunks are typically subsequences of Constituents • Chunks do not cross constituent boundaries 88-680

Chunk Parsing: Accuracy • Chunk parsing achieves higher accuracy • Smaller solution space • Less word-order flexibility within chunks than between chunks • Better locality: • Fewer long-range dependencies • Less context dependence • No need to resolve ambiguity • Less error propagation 88-680

Chunk Parsing: Domain Specificity Chunk parsing is less domain specific: • Dependencies on lexical/semantic information tend to occur at levels "higher" than chunks: • Attachment • Argument selection • Movement • Fewer stylistic differences within chunks 88-680

Chunk Parsing: Efficiency • Chunk parsing is more efficient • Smaller solution space • Relevant context is small and local • Chunks are non-recursive • Chunk parsing can be implemented with a finite state machine 88-680

Psycholinguistic Motivations Chunk parsing is psycholinguistically motivated: • Chunks as processing units • Humans tend to read texts one chunk at a time • Eye-movement tracking studies • Chunks are phonologically marked • Pauses, Stress patterns • Chunking might be a first step in full parsing 88-680

Chunk Parsing Techniques • Chunk parsers usually ignore lexical content • Only need to look at part-of-speech tags • Techniques for implementing chunk parsing: • Regular expression matching / Finite State Machines • Transformation Based Learning • Memory Based Learning • Others 88-680

Regular Expression Matching • Define a regular expression that matches thesequences of tags in a chunk • A simple noun phrase chunk regexp:<DT>? <JJ>* <NN.?> • Chunk all matching subsequences:the/DT little/JJ cat/NN sat/VBD on/IN the/DT mat/NN[the/DT little/JJ cat/NN] sat/VBD on/IN [the/DT mat/NN] • If matching subsequences overlap, the first one gets priority 88-680

Chunking as Tagging • Map Part of Speech tag sequences to {I,O,B}* • I – tag is part of an NP chunk • O – tag is not part of • B – the first tag of an NP chunk which immediately follows another NP chunk • Example: • Input: The little cat sat on the mat • Output: B I I O O B I 88-680

Chunking State of the Art • Depending on task specification and test set: 90-95% 88-680

Homework 88-680

Context Free Grammars • Putting the constituents together • Next Week… 88-680

עיבוד שפות טבעיות - שיעור שבע Partial Parsing