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An improved joint model: POS tagging and dependency parsing

Credit to Download: 1 | Page Numbers 8 | Abstract Views: 58
Year: 2016
COI code: JR_JADM-4-1_001
Paper Language: English

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Authors An improved joint model: POS tagging and dependency parsing

  A. Pakzad - Department of Computer Engineering, Iran University of Science & Technology, Tehran, Iran.
  B. Minaei Bidgoli - Department of Computer Engineering, Iran University of Science & Technology, Tehran, Iran.


Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do the POS tagging task along with dependency parsing in a pipeline mode. Unfortunately, in pipeline models, a tagging error propagates, but the model is not able to apply useful syntactic information. The goal of joint models simultaneously reduce errors of POS tagging and dependency parsing tasks. In this research, we attempted to utilize the joint model on the Persian and English language using Corbit software. We optimized the model s features and improved its accuracy concurrently. Corbit software is an implementation of a transition-based approach for word segmentation, POS tagging and dependency parsing. In this research, the joint accuracy of POS tagging and dependency parsing over the test data on Persian, reached 85.59% for coarse-grained and 84.24% for fine-grained POS. Also, we attained 76.01% for coarse-grained and 74.34% for fine-grained POS on English.


Joint model, Part-Of-Speech, Dependency Parsing, Persian Language

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COI code: JR_JADM-4-1_001

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Pakzad, A. & B. Minaei Bidgoli, 2016, An improved joint model: POS tagging and dependency parsing, Journal of Artificial Intelligence & Data Mining 4 (1), the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Pakzad, A. & B. Minaei Bidgoli, 2016)
Second and more: (Pakzad & Minaei Bidgoli, 2016)
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The University/Research Center Information:
Type: state university
Paper No.: 20397
in University Ranking and Scientometrics the Iranian universities and research centers are evaluated based on scientific papers.

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