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1 CONTEXT-FREE GRAMMARS. NLE 2 Syntactic analysis (Parsing) S NPVP ATNNSVBD NP AT NNthechildrenate thecake.

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Presentation on theme: "1 CONTEXT-FREE GRAMMARS. NLE 2 Syntactic analysis (Parsing) S NPVP ATNNSVBD NP AT NNthechildrenate thecake."— Presentation transcript:


2 NLE 2 Syntactic analysis (Parsing) S NPVP ATNNSVBD NP AT NNthechildrenate thecake

3 NLE 3 Goals of syntactic analysis For deeper understanding To identify TERMS – E.g., in information retrieval In lexical acquisition, to identify GRAMMATICAL RELATIONS For grammar checking For generation

4 NLE 4 Beyond regular languages: Context-Free Grammars S  NP VP NP  Det Nominal Nominal  Noun VP  V Det  the Det  a Noun  flight V  left

5 NLE 5 Derivations A DERIVATION of a string is a sequence of rule applications – E.g., the string “a flight” can be derived from the grammar above and symbol NP by the (leftmost first) derivation NP => Det Nominal => a Nominal => a Noun => a flight Derivations can be visualized as PARSE TREES The LANGUAGE defined by a CFG is the set of strings derivable from the start symbol S (for Sentence)

6 NLE 6 Derivations and parse trees

7 NLE 7 A more formal definition A CFG is a 4-tuple consisting of

8 NLE 8 What `context free’ means

9 NLE 9 Derivations and languages The language L G GENERATED by a CFG grammar G is the set of strings of TERMINAL symbols that can be derived from the start symbol S using the production rules in G – L G = {w | w is in  * and S derives w} The strings in L G are called GRAMMATICAL The strings not in L G are called UNGRAMMATICAL

10 NLE 10 Grammar development One of the most basic skills in NLE is the ability to write a CFG for some fragment of a language (e.g., the dates) We’ll briefly cover some of the issues to be addressed when writing small CFG grammars

11 NLE 11 An example lexicon

12 NLE 12 An example grammar

13 NLE 13 A simple parse tree

14 NLE 14 Basic types of phrases Sentences Noun Phrases Verb phrases Prepositional phrases

15 NLE 15 Basic types of sentences

16 NLE 16 Noun phases: premodifiers NP  (Det) (Card) (Ord) (Quant) (AP) Nominal Det: Determiners – a flight – Optional: I’m looking for flights to Denver Card: Cardinal numbers (one stop) Ord: Ordinal numbers (the first flight) Quantifiers: most flights to Denver leave in the morning AP (Adjectives): three very expensive seats

17 NLE 17 Noun phases: postmodifiers Nominal  Noun Nominal  Nominal PP (PP) (PP) Nominal  Nominal GerundVP Nominal  Nominal RelClause

18 NLE 18 Types of postnominal modifiers

19 NLE 19 Recursion Nominal  Nominal PP (PP) (PP) – Is an example of RECURSIVE rule Other examples: – NP  NP PP – VP  VP PP Recursion a powerful device, but could have bad consequences (see lectures on parsing)

20 NLE 20 Recursion and VP attachment

21 NLE 21 Coordination NP  NP and NP – John and Mary left VP  VP and VP – John talks softly and carries a big stick S  S and / but / S – Kim is a lawyer but Sandy is reading medicine. In fact, probably English has a – XP  XP and XP rule

22 NLE 22 Agreement This dog Those dogs *This dogs *Those dogs This dog is smart *This dog are smart *Those dogs is smart

23 NLE 23 Syntactic analysis with DFA?

24 NLE 24 CFGs vs Regular languages For many applications, finite state languages (the languages defined by FA) are appropriate Limitation of FAs: cannot count – I.e., cannot check A n B n Example of construction showing that English is CF: long-distance dependencies – Which film did Kim say the director who we just met _ recommended _?

25 NLE 25 The Chomsky Hierarchy Finite-state languages (type 3) – A  bC | Cb (a single NT on the right) Context-free languages (type 2) – A  BB Context-sensitive languages (type 1) – CAC  BB Recursively enumerable languages – Every language that can be specified by a finite algorithm

26 NLE 26 Readings Jurafsky and Martin, chapter 9 The chapters on context-free languages in – The Free Dictionary: free%20language free%20language – Wikipedia:

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