ACL RD-TEC 1.0 Summarization of W01-0707

Paper Title:
PROBABILISTIC MODELS FOR PP-ATTACHMENT RESOLUTION AND NP ANALYSIS

Authors: Eric Gaussier and Nicola Cancedda

Other assigned terms:

  • adjective
  • annotation
  • approach
  • attachment site
  • bigram
  • candidate term
  • case
  • compounds
  • conditional probability
  • context-free grammars
  • data sparseness
  • data sparseness problem
  • decision rule
  • dependency link
  • dependency relations
  • determiner
  • distribution
  • estimation
  • events
  • fact
  • frame
  • french
  • french language
  • function words
  • generation
  • grammars
  • grammatical information
  • head word
  • heuristics
  • hypothesis
  • implementation
  • independence assumption
  • index
  • information sources
  • knowledge
  • lexeme
  • lexemes
  • lexical information
  • lexical resources
  • lexicon
  • likelihood
  • linear order
  • linguistic
  • linguists
  • markov chain
  • method
  • model parameters
  • nouns
  • nucleus
  • parse
  • parse table
  • part-ofspeech
  • parts-of-speech
  • pos category
  • pp attachment
  • pp-attachment
  • preposition
  • preposition attachment
  • prepositional attachment
  • prepositional phrases
  • prepositions
  • prior probability
  • priori
  • probabilistic model
  • probabilistic models
  • probabilities
  • probability
  • probability estimates
  • procedure
  • pronoun
  • relation
  • semantic
  • semantic class
  • semantic classes
  • semantic information
  • semantic lexicon
  • sentence
  • sentences
  • sparseness problem
  • statistics
  • subcategorization frame
  • subcategorization frames
  • subcategorization information
  • subtree
  • syntactic structure
  • term
  • terms
  • test data
  • tokens
  • training
  • training and test data
  • training corpus
  • training data
  • trees
  • uniform distribution
  • verb
  • word
  • word level
  • word sequence
  • wordnet
  • words
  • world knowledge

Extracted Section Types:


This page last edited on 10 May 2017.

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