[PDF] Top 20 Head Driven Statistical Models for Natural Language Parsing
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Head Driven Statistical Models for Natural Language Parsing
... One way to overcome these sparse-data problems is to break down the gener- ation of the RHS of each rule into a sequence of smaller steps, and then to make independence assumptions to reduce the number of parameters in ... See full document
49
An Alternative to Head Driven Approaches for Parsing a (Relatively) Free Word Order Language
... heads, Head-Driven (HD) models have been proposed by (Magerman, 1995; Char- niak, 1997; Collins, ...the head daughter is generated first, con- ditioned on properties of the mother ...the ... See full document
10
Book Reviews: Statistical Language Learning
... "Towards history-based grammars: Using richer models for probabilistic parsing." In Speech and Natural Language: Proceedings of a Workshop Held at Harriman, New York.. San Francisco, Cal[r] ... See full document
9
Discriminative Reranking for Natural Language Parsing
... baseline statistical parser is used to generate N-best output both for its training set and for test data ...log-linear models of Ratnaparkhi, Roukos, and Ward (1994), Papineni, Roukos, and Ward (1997, ... See full document
46
Modern Natural Language Interfaces to Databases: Composing Statistical Parsing with Semantic Tractability
... P RECISE takes as input a lexicon and a parser. Then, given an English question, P RECISE maps it to one (or more) corresponding SQL queries. We concisely review how P RECISE works through a simple example. Consider the ... See full document
7
A Survey of Natural Language Query Builder Interface for Structured Databases using Dependency Parsing
... In Natural Language Processing a common set of characteristics can be generally assumed about the used grammars: the lexical items that define the nodes are the word forms; the parsing is concerned ... See full document
6
Head Driven Parsing for Word Lattices
... Most models are evaluated ei- ther with measures of success for parsing or for word recognition, but rarely ...both. Parsing mod- els are difficult to implement as word-predictive language ... See full document
8
An Efficient Natural Language Processing System Specially Designed for the Chinese Language
... In Test III, the present head-driven parsing strategy based on the direction-selective chart was used without any look-ahead capability, and finally in Test IV, the present head-driven p[r] ... See full document
28
A Fully Statistical Approach to Natural Language Interfaces
... Conclusion We have presented a fully trained statistical natural language interface system, with separate models corresponding to the classical processing steps of parsing, semantic inte[r] ... See full document
7
Active Learning for Statistical Natural Language Parsing
... to statistical parsing, where two component models are trained and the most confident parsing outputs of the existing model are incorporated into the next ...improve statistical parsers ... See full document
8
Efficient combinator parsing for natural-language.
... A parsing method, which is constructed using these combinators, is called ‘combinatory-parsing’ (as higher-order functions ‘combine’ different parsers ...complete language-processor can be ... See full document
112
Comparing Local and Sequential Models for Statistical Incremental Natural Language Understanding
... We see that the results for ATIS are considerably lower than the state of the art in statistical NLU (Table 1). This need not concern us too much here, as we are mostly interested in the dynam- ics of the ... See full document
8
Analysis of Statistical Parsing in Natural Language Processing
... Part-of-speech tagging is the process of assigning a part-of-speech (such as a noun, verb, pronoun, preposition, adverb, and adjective), to each word in a sentence. The input to a tagging algorithm is the sequence of ... See full document
6
Statistical Decision Tree Models for Parsing
... Evaluating SPATTER against the Penn Treebank Wall Street Journal corpus using the PARSEVAL measures, SPATTER achieves 86% precision, 86% recall, and 1.3 crossing brackets per sentence fo[r] ... See full document
8
Applying a Grammar Based Language Model to a Simplified Broadcast News Transcription Task
... of the adjective type (participle or non-participle and attributive, adverbial or predicative) and the proba- bility of its length in words given the adjective type. This allows the model to directly penalize long ad- ... See full document
8
Corpus Variation and Parser Performance
... of natural language parsing, through the use of statistical methods trained using large corpora of hand-parsed training ...quantitative parsing results have been reported on other ... See full document
6
Head driven Transition based Parsing with Top down Prediction
... Figure 5 presents the parsing time against sen- tence length. Our proposed top-down parser is the- oretically slower than shift-reduce parser and Fig- ure 5 empirically indicates the trends. The domi- nant factor ... See full document
9
Compositional pre training for neural semantic parsing
... the parsing and to- ken accuracy reported for three standard semantic parsing datasets in (Jia and Liang, ...2016). Parsing accuracy is defined as the proportion of the pre- dicted logical forms that ... See full document
7
Head Driven Phrase Structure Grammar Parsing on Penn Treebank
... Each node in the HPSG tree noted as AVM repre- sents compound structure. Even in our simplified HPSG, each phrase (span) should be companied with its head. To facilitate the processing of ex- isting parsers, we ... See full document
13
Language Based Environment for Natural Language Parsing
... In the Figure 2 states labelled "BUILD PHRASE ON RIGHT" and "FIND REGENT ON RIGHT" push the verb to the left stack and pop the right stack for the current constituent.. When the verb is [r] ... See full document
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