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Shallow parsing

About: Shallow parsing is a research topic. Over the lifetime, 397 publications have been published within this topic receiving 10211 citations.


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Book ChapterDOI
15 Feb 2004
TL;DR: A statistical translation model incorporating linguistic knowledge of syntactic and phrasal information for better translations is presented and it is shown that the structural relationship helps construct a better translation model for structurally different languages like Korean and English.
Abstract: As a part of work on alignment of the English and Korean parallel corpus, this paper presents a statistical translation model incorporating linguistic knowledge of syntactic and phrasal information for better translations. For this, we propose three models: First, we incorporate syntactic information such as part of speech into the word-based lexical alignment. Based on this model, we propose the second model which finds phrasal correspondence in the parallel corpus. Phrasal mapping through chunk-based shallow parsing enables to settle mismatch of meaningful units in the two languages. Lastly, we develop a two-level alignment model by combining these two models in order to construct both the word and phrase-based translation model. Model parameters are automatically estimated from a set of bilingual sentence pairs by applying the EM algorithm. Experiments show that the structural relationship helps construct a better translation model for structurally different languages like Korean and English.
Journal ArticleDOI
TL;DR: In this essay, some applied technology of shallow parsing is introduced and a new method of it is experimented.
Abstract: Shallow parsing is a new strategy of language processing in the domain of natural language processing recently years It is not focus on the obtaining of the full parsing tree but requiring of the recognition of some simple composition of some structure It separated parsing into two subtasks: one is the recognition and analysis of chunks the other is the analysis of relationships among chunks In this essay, some applied technology of shallow parsing is introduced and a new method of it is experimented
Book ChapterDOI
23 Oct 2006
TL;DR: In the belief that punctuation can aid in the process of sentence structure analysis, this work focuses on a prior assignment of values to commas in Spanish texts, with very encouraging results.
Abstract: In the belief that punctuation can aid in the process of sentence structure analysis, our work focuses on a prior assignment of values to commas in Spanish texts. Supervised machine learning techniques are applied for learning commas classifiers, taking as input attributes positional information and part of speech tags. One of these comma classifiers and a rule-based analyzer are combined in order to recognize and label text structures. The prior assignment of values to commas allowed the simplification of recognition rules, with very encouraging results.
Proceedings ArticleDOI
30 Nov 2009
TL;DR: A new approach to natural-language chunking using an evolutionary model that uses previously captured training information to guide the evolution of the model and a multi-objective optimization strategy is used to produce the best solutions based on the internal and the external quality of chunking.
Abstract: In this work, a new approach to natural-language chunking using an evolutionary model is proposed. This uses previously captured training information to guide the evolution of the model. In addition, a multi-objective optimization strategy is used to produce the best solutions based on the internal and the external quality of chunking. Experiments and the main results obtained using the model and state-of-the-art approaches are discussed.

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20217
202012
20196
20185
201711
201611