Results 21 to 30 of about 6,924 (296)
Improving Persian Dependency-Based Parser Using Deep Learning [PDF]
Computer and Knowledge Engineering, 2022 One of the most important problems in computational linguistics is the grammar and, consequently, syntactic structures and structural parsing. The structural parser tries to analyze the relationships between words and to extract the syntactic structure ...
soghra lazemi +2 more
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Computational Intelligence, 2014 Dependency parsers, which are widely used in natural language processing tasks, employ a representation of syntax in which the structure of sentences is expressed in the form of directed links (dependencies) between their words. In this article, we introduce a new approach to transition‐based dependency parsing in which the parsing algorithm does not ...
Gómez Rodríguez, Carlos +2 more
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Wide-coverage deep statistical parsing using automatic dependency structure annotation [PDF]
, 2008 A number of researchers (Lin 1995; Carroll, Briscoe, and Sanfilippo 1998; Carroll et al. 2002; Clark and Hockenmaier 2002; King et al. 2003; Preiss 2003; Kaplan et al. 2004;Miyao and Tsujii 2004) have convincingly argued for the use of dependency (rather
O'Donovan, Ruth +6 more
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Dependency Parsing for Arabic Quran using Easy-First Parsing Algorithm
Edumatic, 2020 Arabic is the main language of Al-Quran. Nowadays, many people are studying the Language of Al-Quran, called Quran Arabic. For the beginners, it is important for them to understand the syntactic relationship in a sentence found in the Qur'an.
Alfiya El Hafsa +2 more
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The domain dependence of parsing [PDF]
Proceedings of the fifth conference on Applied natural language processing -, 1997 A major concern in corpus based approaches is that the applicability of the acquired knowledge may be limited by some feature of the corpus, in particular, the notion of text 'domain'. In order to examine the domain dependence of parsing, in this paper, we report 1) Comparison of structure distributions across domains; 2) Examples of domain specific ...
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Strictly lexical dependency parsing [PDF]
Proceedings of the Ninth International Workshop on Parsing Technology - Parsing '05, 2005 We present a strictly lexical parsing model where all the parameters are based on the words. This model does not rely on part-of-speech tags or grammatical categories. It maximizes the conditional probability of the parse tree given the sentence. This is in contrast with most previous models that compute the joint probability of the parse tree and the ...
Qin Iris Wang +2 more
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Sequence Tagging for Fast Dependency Parsing
Proceedings, 2019 Dependency parsing has been built upon the idea of using parsing methods based on shift-reduce or graph-based algorithms in order to identify binary dependency relations between the words in a sentence.
Michalina Strzyz +2 more
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The Interplay Between Loss Functions and Structural Constraints in Dependency Parsing
Northern European Journal of Language Technology, 2019 Dependency parsing can be cast as a combinatorial optimization problem with the objective to find the highest-scoring graph, where edge scores are learnt from data. Several of the decoding algorithms that have been applied to this task employ structural
Robin Kurtz, Marco Kuhlmann
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Incremental dependency parsing [PDF]
Proceedings of the 30th annual meeting on Association for Computational Linguistics -, 1992 The paper introduces a dependency-based grammar and the associated parser and focusses on the problem of determinism in parsing and recovery from errors. First, it is shown how dependency-based parsing can be afforded, by taking into account the suggestions coming from other approaches, and the preference criteria for parsing are breifly addressed ...
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Investigating multilingual dependency parsing [PDF]
Proceedings of the Tenth Conference on Computational Natural Language Learning - CoNLL-X '06, 2006 In this paper, we describe a system for the CoNLL-X shared task of multilingual dependency parsing. It uses a baseline Nivre's parser (Nivre, 2003) that first identifies the parse actions and then labels the dependency arcs. These two steps are implemented as SVM classifiers using LIBSVM.
Johansson, Richard, Nugues, Pierre
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