منابع مشابه
Shift-Reduce Dependency DAG Parsing
Most data-driven dependency parsing approaches assume that sentence structure is represented as trees. Although trees have several desirable properties from both computational and linguistic perspectives, the structure of linguistic phenomena that goes beyond shallow syntax often cannot be fully captured by tree representations. We present a parsing approach that is nearly as simple as curren...
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A dependency parser analyzes syntactic structure by identifying dependency relations between words. In this lecture, I will introduce dependency-based syntactic representations (§1), arcfactored models for dependency parsing (§2), and online learning algorithms for such models (§3). I will then discuss two important parsing algorithms for these models: Eisner’s algorithm for projective dependen...
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Dependency parsing has been a prime focus of NLP research of late due to its ability to help parse languages with a free word order. Dependency parsing has been shown to improve NLP systems in certain languages and in many cases is considered the state of the art in the field. The use of dependency parsing has mostly been limited to free word order languages, however the usefulness of dependenc...
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Parsing unrestricted text is useful for many language technology applications but requires parsing methods that are both robust and efficient. MaltParser is a language-independent system for data-driven dependency parsing that can be used to induce a parser for a new language from a treebank sample in a simple yet flexible manner. Experimental evaluation confirms that MaltParser can achieve rob...
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ژورنال
عنوان ژورنال: Journal of Natural Language Processing
سال: 2011
ISSN: 1340-7619
DOI: 10.5715/jnlp.18.351