st madar 2019 shared task arabic fine grained dialect identification

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Lexical Diversity in Kinship Across Languages and Dialects

Languages are known to describe the world in diverse ways. Across lexicons, diversity is pervasive, appearing through phenomena such as lexical gaps and untranslatability. However, in computational resources, such as multilingual lexical databases, diversity is hardly ever represented. In this paper, we introduce a method to enrich computational lexicons with content relating to linguistic diversity. The method is verified through two large-scale case studies on kinship terminology, a domain known to be diverse across languages and cultures: one case study deals with seven Arabic dialects, while the other one with three Indonesian languages. Our results, made available as browseable and downloadable computational resources, extend prior linguistics research on kinship terminology, and provide insight into the extent of diversity even within linguistically and culturally close communities

trentoteam at semeval 2017 task 3 an application of grice maxims in ranking community question answers

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mawdoo3 ai at madar shared task arabic fine grained dialect identification with ensemble learning

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A systematic Approach towards the Solution of the Polysemy Problem in Natural Language Processing

WordNet has been used widely in NLP and semantic applications. Despite the reputation of WordNet, it still suffers from many problems that make it hard to be usable by NLP and semantic applications. The major problem that has been extensively researched last decades is polysemy. Solving the polysemy problem is indispensable because the high polysemous nature of WordNet leads to insufficient quality of NLP and semantic applications results. In this proposal, we describe the polysemy problem, report the state of the art approaches, and introduce a novel approach for solving polysemy

An Organizational Approach to the Polysemy Problem in WordNet

Polysemy in WordNet corresponds to various kinds of linguistic phenomena that can be grouped into five classes. One of them is homonymy that refers to the cases, where the meanings of a term are unrelated, and three of the classes refer to the polysemy cases, where the meanings of a term are related. These three classes are specialization polysemy, metonymy, and metaphoric polysemy.Another polysemy class is the compound noun polysemy. In this thesis, we focus on compound noun polysemy and specialization polysemy. Compound noun Polysemy corresponds to the cases, where we use the modified noun to refer to a compound noun. Specialization polysemy is a type of related polysemy referring to the polysemy cases, when a term is used to refer to either a more general meaning or a more specific meaning. Compound noun polysemy and specialization polysemy in WordNet are considered the main reasons behind the highpolysemous nature of WordNet that make WordNet redundant and too fine grained for natural language processing. Another problem in WordNet is its polysemy representation. WordNet represents the polysemous terms by capturing the different meanings of them at lexical level but without giving emphasis on the polysemy classes these terms belong to. The highpolysemous nature and the polysemy representation in WordNet affect the usability of it as suitable knowledge representation resource for natural language processing applications. In fact, the polysemy problem in WordNet is a challenging problem for natural language processing applications, especially in the field of information retrieval and semantic search. To solve this problem, many approaches have been suggested. Although all the state of the art approaches are good to solve the polysemy problem partially, they do not give a general solution for it. In this thesis, we propose a novel approach to solve the compound noun and specialization polysemy problem in WordNet in the case of nouns. Solving the compound noun polysemy and the specialization polysemy problem is an important step that enhances the usability of WordNet as a knowledge representation resource. The proposed approach is not an alternative to the existing approaches. It is a complementary solution for the state of the art approaches especially the systematic polysemy approaches

Lexical diversity in kinship across languages and dialects

Languages are known to describe the world in diverse ways. Across lexicons, diversity is pervasive, appearing through phenomena such as lexical gaps and untranslatability. However, in computational resources, such as multilingual lexical databases, diversity is hardly ever represented. In this paper, we introduce a method to enrich computational lexicons with content relating to linguistic diversity. The method is verified through two large-scale case studies on kinship terminology, a domain known to be diverse across languages and cultures: one case study deals with seven Arabic dialects, while the other one with three Indonesian languages. Our results, made available as browseable and downloadable computational resources, extend prior linguistics research on kinship terminology, and provide insight into the extent of diversity even within linguistically and culturally close communities.</jats:p