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Bootstrapping parsers via syntactic projection across parallel texts
Broad coverage, high quality parsers are available for only a handful of languages. A prerequisite for developing broad coverage parsers for more languages is the annotation of text with the desiredExpand
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Just How Mad Are You? Finding Strong and Weak Opinion Clauses
There has been a recent swell of interest in the automatic identification and extraction of opinions and emotions in text. In this paper, we present the first experimental results classifying theExpand
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Evaluating Translational Correspondence using Annotation Projection
Recently, statistical machine translation models have begun to take advantage of higher level linguistic structures such as syntactic dependencies. Underlying these models is an assumption about theExpand
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Bootstrapping statistical parsers from small datasets
We present a practical co-training method for bootstrapping statistical parsers using a small amount of manually parsed training material and a much larger pool of raw sentences. Experimental resultsExpand
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Sample Selection for Statistical Parsing
  • Rebecca Hwa
  • Computer Science
  • Computational Linguistics
  • 1 September 2004
Corpus-based statistical parsing relies on using large quantities of annotated text as training examples. Building this kind of resource is expensive and labor-intensive. This work proposes to useExpand
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A Re-examination of Machine Learning Approaches for Sentence-Level MT Evaluation
Recent studies suggest that machine learning can be applied to develop good automatic evaluation metrics for machine translated sentences. This paper further analyzes aspects of learning that impactExpand
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Sample Selection for Statistical Grammar Induction
Corpus-based grammar induction relies on using many hand-parsed sentences as training examples. However, the construction of a training corpus with detailed syntactic analysis for every sentence is aExpand
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Regression for Sentence-Level MT Evaluation with Pseudo References
Many automatic evaluation metrics for machine translation (MT) rely on making comparisons to human translations, a resource that may not always be available. We present a method for developingExpand
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RECOGNIZING STRONG AND WEAK OPINION CLAUSES
There has been a recent swell of interest in the automatic identification and extraction of opinions and emotions in text. In this paper, we present the first experimental results classifying theExpand
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Example Selection for Bootstrapping Statistical Parsers
This paper investigates bootstrapping for statistical parsers to reduce their reliance on manually annotated training data. We consider both a mostly-unsupervised approach, cotraining, in which twoExpand
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