Special Electives of Comp.Linguistics: Processing Anaphoric Expressions

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Special Electives of Comp.Linguistics
Processing Anaphoric Expressions

• Eleni Miltsakaki
• AUTH
• Fall 2005-Lecture 1

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Lets introduce ourselves

• Course Special Electives of CL Processing
  Anaphoric Expressions (Ling 2-342)
• Meeting times Friday 1100-1400
• Office hours Friday 930-1100
• Prof Eleni Miltsakaki
• BA Aristotle University -- English American
  Lang. Lit.
• MA University of Essex, UK -- Applied Linguistics
• PhD University of Pennsylvania, USA --
  Theoretical and Computational Linguistics
• Email elenimi_at_enl.auth.gr http//www.cis.upenn
  .edu/elenimi
• Students ?

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Brief outline

• What is computational linguistics (CL)?
• Why is it hard for computers to understand human
  languages?
• What are some practical applications of CL?
• What we will do in this course?
• What is anaphora and anaphor resolution?
• Why is it hard?
• Tentative syllabus and course projects

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What is Computational Linguistics?

• A discipline between Linguistics and Computer
  Science
• Concerned with the computational aspects of human
  language processing
• Has theoretical and applied components

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Theoretical CL

• Formal theories about the linguistic knowledge
  that a human needs for generating and
  understanding language
• Simulation of aspects of the human language
  faculty and their implementation as computer
  programs
• Overlaps and collaborates with Theoretical
  Linguistics, Computer Science, Psycholinguistics

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Applied CL

• Focuses on the practical outcome of modeling
  human language use
• aka language engineering or human language
  technology
• Existing CL systems are far from achieving human
  ability but there are numerous possible and
  useful applications
• Question/answering, summarization, translation,
  computer agents, educational applications etc

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Why is language so difficult for a computer?

• AMBIGUITY!
• Natural languages are massively ambiguous at all
  levels of processing (but humans dont even
  notice)
• To resolve ambiguity, humans employ not only a
  detailed knowledge of the language -- sounds,
  phonological rules, grammar, lexicon etc -- but
  also
• Detailed knowledge of the world (e.g. knowing
  that apples can have bruises but not smiles, or
  that snow falls but London does not).
• The ability to follow a 'story', by connecting up
  sentences to form a continuous whole, inferring
  missing parts.
• The ability to infer what a speaker meant, even
  if he/she did not actually say it.
• It is these factors that make NLs so difficult to
  process by computer -- but therefore so
  fascinating to study.

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Syntactic ambiguity

• I saw her duck
• The man closed the door with a bang
• The man closed the door with the black and white
  stripes
• I saw the man with the telescope

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Semantic ambiguity

• The man went over to the bank
• Mary loved Bill. Mary loved potato chips.
• Water runs down the hill. The road runs down the
  hill

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Phonological ambiguity

• Within words
• Input, intake, income
• Imput, intake, iNcome (Nng)
• Across word boundaries
• When playing football, watch the referee
• When talking about other people, watch whos
  listening
• When catching a hard ball, wear gloves
• Homophones
• Im a writer and I write books
• Im a rider and I write books

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Discourse

• Anaphora
• London had snow yesterday
• It also had fog
• It fell to a depth of one meter
• It will continue cold today
• Speaker intentions
• Can you swim
• Can you tell me the time?
• Can you pass the salt?
• Inference
• You shouldnt lend John any books. He never
  returns them.

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Language technology

• ALICE the chatbox
• http//www.alicebot.org/
• Jabberwacky
• http//www.jabberwacky.com/
• USC demo for learning Arabic
• http//www.isi.edu/7Ejmoore/Mankin/MankinTLWeb.mo
  v

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Anaphoric uses of pronouns

• Bound variables Non-referring
• Referential pronouns Reference to a contextually
  salient individual
• Deixis
• Co-reference

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Bound variables

• Non-referring pronouns
• This type of pronoun does not refer to an
  individual
• Non-referring pronouns are interpreted according
  to rules in the grammar
• (1) Every man put a screen in front of him.

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Referential pronouns (1)

• Deictic
• (uttered immediate after a certain man left the
  room)
• (2) Im glad hes gone!

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Referential pronouns (2)

• Coreference
• (3) I dont think anybody here is interested in
  Smiths work. He should not be invited.
• (4) Most accidents that Mary reported were causes
  by her cat

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• In this course we will focus on understanding how
  we interpret
• referential pronouns

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Basic theoretical models

• Structural focusing (Grosz, Joshi Weinstein,
  1983/1995)
• Centering relating discourse structure,
  discourse coherence and choice of referring
  expression.
• (11) John helped George wash the car.
• (12) He washed the windows and George waxed
  the car.
• (13) He soaped a pane/He buffed the hood
• Semantic/pragmatic focusing (Stevenson et al,
  1994/2000)
• Verbs and connectives have focusing properties
• (14) John criticized Bill because he failed
  to correct his faults

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Challenges

• 1. Max is waiting for Fred.
• 2. He invited him for dinner.
• (Brennan et al, 1987)
• 3. Dodge was robbed by an ex convict.
• The ex-convict tied him up
• because he wasn't cooperating.
• Then he took all the money and ran
• (Suri et al, 1999)

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continued

• 7. John criticized Bill, so he tried to correct
  the fault.
• 8. Bill was criticized by John so he tried to
  correct the fault
• 9. John criticized Bill.
• Next, he insulted Susan.
• (Stevenson et al, 2000)

• 10. Max despises Ross
• a. He always gives Ross
• a hard time. (easy)
• b. He always gives Max
• a hard time. (hard)
• (DZmura and Tanenhaus, 1998)

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• How can we find out what people do when assigning
  the correct interpretation to pronouns?
• Are there cross-linguistic differences?

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Some methodological approaches

• Corpus based investigation
• Experimental
• Statistical

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Tentative syllabus

• Theories of pronoun interpretation (6)
• Linguistic/Cross linguistic
• Computational
• Psycholinguistic
• Background readings for student projects (2)
• Lab work (2)
• Current systems for anaphora resolution (2)
• Review (1)

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Course projects

• You can pick either a corpus-based or
  experimental method to investigate some aspects
  of pronoun resolution in English or Greek or both

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Evaluation

• 3 tests/homeworks (30)
• Mid-term exam (30)
• Course project (40)