Implementation of nlization framework for verbs, pronouns and determiners with eugene
Harinder Singh, Parteek Kumar

TL;DR
This paper presents a framework using EUGENE for natural language generation from UNL semantic networks, focusing on verbs, pronouns, and determiners for Punjabi, facilitating language-independent machine translation.
Contribution
It introduces a NLization framework with EUGENE for Punjabi, detailing how UNL inputs are syntactically and semantically analyzed for natural language generation.
Findings
Successful NLization of Punjabi sentences involving verbs, pronouns, and determiners.
Demonstrates language independence of the EUGENE NLizer with proper parametrization.
Provides a detailed methodology for analyzing UNL inputs for Punjabi language generation.
Abstract
UNL system is designed and implemented by a nonprofit organization, UNDL Foundation at Geneva in 1999. UNL applications are application softwares that allow end users to accomplish natural language tasks, such as translating, summarizing, retrieving or extracting information, etc. Two major web based application softwares are Interactive ANalyzer (IAN), which is a natural language analysis system. It represents natural language sentences as semantic networks in the UNL format. Other application software is dEep-to-sUrface GENErator (EUGENE), which is an open-source interactive NLizer. It generates natural language sentences out of semantic networks represented in the UNL format. In this paper, NLization framework with EUGENE is focused, while using UNL system for accomplishing the task of machine translation. In whole NLization process, EUGENE takes a UNL input and delivers an output in…
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling
