Abstract
The people in Bangladesh and two states (i.e., Tripura and West Bengal) in India, which is about 230 million of the world population, use Bengali as their first dialect. However, very few numbers of resources and tools are available for this language. This paper presents a Bangla DeConverter to extract Bangla texts from Universal Networking Language (UNL). It explains and illustrates the different phases of the proposed Bangla DeConverter. The syntactic linearization, the implementation of the results of the proposed Bangla DeConverter, and the extraction of a Bangla sentence from UNL expressions are presented in this paper. The Bangla DeConverter has been tested on UNL expressions of 300 Bangla sentences using a Russian and English Language Server. The proposed system generates 90% syntactically and semantically correct Bangla sentences with a UNL Bilingual Evaluation Understudy (BLEU) score of 0.76.
Highlights
The Universal Networking Language (UNL) [1] is a digital language in the form of a network of semantic words that performs as an intermediate representation to expose and interchange all types of knowledge and information
The UNL expression of the sentence, I will go to office after eating rice is shown in (18) using Russian English Language Server
Our projected system was tested by converting a set of 300 Bangla sentences into their corresponding set of UNL expressions using a Russian–English Language server [18]
Summary
The Universal Networking Language (UNL) [1] is a digital language in the form of a network of semantic words that performs as an intermediate representation to expose and interchange all types of knowledge and information. English is a fixed word order language that follows the subject, verb, and object (SVO) pa ern. For conversion of a source language to UNL and from UNL to a target language, EnCo and DeCo tools need to be developed. These tools execute their tasks based on a word dictionary and a set of analysis and generation rules for a given language [1]. Information 2019, 10, x FOR PEER REVIEW green’ and the corresponding UNL graph shown in Figure 1.Here, obj_indicates object relation, src_for source. Obj_indicates object relation, src_for source (initial state) relation, and gol_for goal (final state), respectively
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