ACL RD-TEC 1.0 Summarization of W01-0704

Paper Title:
SEMANTIC PATTERN LEARNING THROUGH MAXIMUM ENTROPY-BASED WSD TECHNIQUE

Authors: MaximilianoSaiz-Noeda and Armando Suárez and Manuel Palomar

Other assigned terms:

  • 10-fold cross-validation
  • ambiguity
  • anaphor
  • anaphora
  • anaphors
  • annotated corpus
  • approach
  • brown corpus
  • case
  • coefficient
  • comprehension
  • concept
  • concepts
  • conditional probability
  • conditional probability model
  • content words
  • corpora
  • dependency tree
  • dependency trees
  • device
  • discourse
  • distribution
  • english corpus
  • entropy
  • entropy models
  • error rate
  • estimation
  • feature
  • function words
  • generation
  • head word
  • heterogeneous information
  • implementation
  • information source
  • information sources
  • knowledge
  • language processing tasks
  • lexical database
  • lexical resources
  • linguistic
  • linguistic knowledge
  • linguistics
  • maximum entropy models
  • method
  • morpho-syntactic information
  • morphological features
  • names
  • natural language
  • natural language processing tasks
  • nlp task
  • nlp tasks
  • nouns
  • ontologies
  • ontology
  • parsing tree
  • parts of speech
  • precision
  • probabilities
  • probability
  • probability distribution
  • probability model
  • procedure
  • process
  • processing tasks
  • pronoun
  • proposition
  • query
  • relation
  • resolution problem
  • semantic
  • semantic information
  • semantic pattern
  • semantic relations
  • sentence
  • statistical information
  • synset
  • synsets
  • syntactic information
  • syntactic relation
  • tagged corpora
  • tagged corpus
  • tags
  • target word
  • technique
  • terms
  • text
  • theory
  • topics
  • training
  • training corpus
  • training data
  • training set
  • tree
  • trees
  • understanding
  • verb
  • west european languages
  • word
  • word sense
  • wordnet
  • words
  • world-knowledge

Extracted Section Types:


This page last edited on 10 May 2017.

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