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THE BIG PICTURE

THE BIG PICTURE. Basic Assumptions. Linguistics is the empirical science that studies language (or linguistic behavior) Linguistics proposes theories (models) that can be verified or falsified against linguistic data

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THE BIG PICTURE

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  1. THE BIG PICTURE

  2. Basic Assumptions • Linguistics is the empiricalscience that studies language (or linguistic behavior) • Linguistics proposes theories (models) that can be verified or falsified against linguistic data • Computational linguistics is the branch of linguistics that uses computational models • Natural language processing (NLP) is the engineering equivalent of computational linguistics (as civil engineering is to physics)

  3. Empirical Matter The Big Picture ? • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models ? Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the ? ? Linguistic Theory

  4. Brain Scans Grammaticality Judgments Psycholinguistic Experiments Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the fan Corpora Empirical Matter: Language and/or Linguistic Behavior

  5. Empirical Matter: Language and/or Linguistic Behavior (?) Brain Scans Grammaticality Judgments Psycholinguistic Experiments Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the fan Corpora

  6. Underlying Empirical Object of Study • What is linguistics really “about”? • The brain (cognitive science) • Language as an abstract structure (structuralism)

  7. or Empirical Matter The Big Picture • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models ? Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the ? ? Linguistic Theory

  8. Data Structures Phrase-structure trees Dependency trees Dags … Mathematical Formalisms (1) • Formalisms • CFG • TAG • Dependency grammars • Unification grammars • … • Algorithms • Chart parsing • Bottom-up • Top-down • … • Deterministic parsing • LR • … • Generation • … • Distributional Models • Probabilistic CFG • Probabilistic TAG • …

  9. Exist in formal computer science, mathematics, statistics… Exist independently of natural language Do not on their own attempt to model or explain natural language Do not on their own succeed in modeling or explaining natural language Mathematical Formalisms (2)

  10. or Empirical Matter The Big Picture • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the ? ? Linguistic Theory

  11. Linguistic Theory • Phonetics: articulated sounds • Phonology: how do sounds form minimal meaning units (morphemes)? • Morphology: how do morphemes form words? • Syntax: how do words form utterances? • Semantics: what is the meaning of utterances? • Pragmatics: in what context do we use which utterance?

  12. Goal of Syntactic Theory (1) • Goal (version 1): formulate theory of how words form utterances (sentences, in written language) • Goal (version 2): formulate theory of how words in linear sequence combine to form utterances • Utterance represented by non-linear structure (e.g., a tree)

  13. Goal of Syntactic Theory (2) • Goal (version 3): formulate theory of how words in linear sequence correspond to structures • Assumption: semantics interprets this structure as meaning -- in particular, predicate-argument structure • Goal (version 4): formulate theory of how words in linear sequence correspond to predicate-argument structures

  14. seem like John apples Goal of Syntactic Theory (3) • What is predicate-argument structure? John seems to like apples • Deep dependency-like structure!

  15. Goal of Syntactic Theory (4) • So what role does phrase-structure play? • “Augmented” representation of linear order S NP Vi John V S seems Vi NP t V NP like apples

  16. Goal of Syntactic Theory (5) • Goal (version 5, final for us): formulate theory of how phrase structure of sentences relates to their deep dependency • Goal (version 5 – dependency theories): formulate theory of how surface dependency of sentences relates to their deep dependency

  17. or Empirical Matter The Big Picture • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the ? theory of Linguistic Theory

  18. Components of a Syntactic Theory (1) • Definition of surface representation • Choice of data structure/formalism/… • List of node labels, rules, etc. • Definition of deep representation • Choice of data structure/formalism/… • List of node labels, rules, etc. • Description of correspondence • Choice of formal mechanism • List of rules (?)

  19. Components of a Syntactic Theory (2) • Formal Framework • Definition of surface representation • Choice of data structure/formalism/… • Definition of deep representation • Choice of data structure/formalism/… • Description of correspondence • Choice of formal mechanism • Linguistic Content • Definition of surface representation • List of node labels, rules, etc. • Definition of deep representation • List of node labels, rules, etc. • Description of correspondence • List of rules (?)

  20. Empirical Matter The Big Picture or • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the uses theory of • Linguistic Theory • Content • Surface representation (eg, ps) • Deep representation (eg, dep) • Correspondence

  21. Note on Competence vs Performance • Performance: human sentence processing • Language use • Interacts with other parts of cognition: memory, emotions, etc • Studied in psychology, data from experiments • Competence: human knowledge of syntax that allows performance • What we have been and will be talking about in this course, largely • Studied in linguistics, data from grammaticality judgments and corpora • Distinction debatable

  22. Content of aSyntactic Theory (1) • Defeasible predictive theory: • Have theory • Needs to be able to make predictions (=deductions) • Predictions need to be verifiable or falsifiable against empirical matter • When prediction is falsified, theory needs to be changed • Formal framework • And/or linguistic content • “Hypothetico-deductive method” (Popper)

  23. Content of aSyntactic Theory (2) • What exactly is being predicted? • Set of allowable surface representations: • Is predicted sentence in the language? • AND correspondence between surface representation and deep representation: • Is the predicted correspondence plausible? • What is scope of theory? • One language: descriptive theory • All languages: explanatory theory (Chomsky)

  24. Descriptive Theory • Theory for one language, which is fixed • Predicts what surface structures (i.e., strings) are grammatical • Predicts, for a given grammatical string (and its surface representation) its deep representation

  25. Explanatory Theory (1) • Need to predict, given a language, what its surface structures and corresponding deep structures are • Need a parameterized theory • Chomsky (1981, etc): • Principles: things that hold for all languages • Parameters: values differ for different languages • “Principles-and-paremeters” type theory also used by other researchers (TAG, HPSG, LFG)

  26. Explanatory Theory (2) Example

  27. Linguistic Theories and Empiricial Matter • What is predicted? How can the theory be falsified? • Behavior of observable data • What is the theory “about”? • Descriptive theory: language as structure • Explanatory theory: presumably, cognition

  28. Empirical Matter The Big PictureFinal, for now or • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models descriptive theory is about Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the predicts uses explanatory theory is about • Linguistic Theory • Content • Surface representation (eg, ps) • Deep representation (eg, dep) • Correspondence

  29. Empirical Matter The Big PictureFinal, for now or • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models descriptive theory is about Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the predicts uses explanatory theory is about • Linguistic Theory • Content • Surface representation (eg, ps) • Deep representation (eg, dep) • Correspondence In course so far

  30. Empirical Matter The Big PictureFinal, for now or • Formalisms • Data structures • Formalisms • Algorithms • Distributional Models descriptive theory is about Maud expects there to be a riot *Teri promised there to be a riot Maud expects the shit to hit the fan *Teri promised the shit to hit the predicts uses explanatory theory is about • Linguistic Theory • Content • Surface representation (eg, ps) • Deep representation (eg, dep) • Correspondence In rest of course

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