A Fuzzy Approach to Language Universals for NLP

Urrutia, Adrià Torrens; López, María Dolores Jiménez; Brosa-Rodríguez, Antoni

doi:10.1109/fuzz45933.2021.9494516

Cited by 3 publications

(4 citation statements)

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“…For our work, we will take into account the trichotomy of low, medium, high . In this sense, as proposed in [45], the membership scale of universality in linguistic rules recognize: A possible world is defined as a specific context in which a linguistic expression is used. In case of evaluative expressions, it is characterized by a triple w = v L , v S , v R .…”

Section: Fuzzy Natural Logic Computing Universals and Linguistic Comp...mentioning

confidence: 99%

“…Linguistic rules that trigger a low truth value of satisfaction in U-FPGr; therefore, they are found satisfied in almost none of the languages.The value of complexity is obtained from IF − THEN rules such as: Definition 4. We characterize fuzzy IF − THEN rules for complexity as follows:• IF a rule is a High Universal, THEN the value of complexity is low.•IF a rule is a Medium Universal, THEN the value of complexity is medium.•IF a rule is a Low Universal, THEN the value of complexity is high.Similarly, we can express:• IF the value of complexity is high, THEN the rule is a low universal.•IF the value of complexity is medium, THEN the rule is medium universal.•IF the value of complexity is low, THEN the rule is high universal.The membership scale of complexity in linguistic rules is[45]:• Low Complexity.…”

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confidence: 99%

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A Fuzzy Grammar for Evaluating Universality and Complexity in Natural Language

et al. 2022

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The paper focuses on linguistic complexity and language universals, which are two important and controversial issues in language research. A Fuzzy Property Grammar for determining the degree of universality and complexity of a natural language is introduced. In this task, the Fuzzy Property Grammar operated only with syntactic constraints. Fuzzy Natural Logic sets the fundamentals to express the notions of universality and complexity as evaluative expressions. The Fuzzy Property Grammar computes the constraints in terms of weights of universality and calculates relative complexity. We present a proof-of-concept in which we have generated a grammar with 42B syntactic constraints. The model classifies constraints in terms of low, medium, and high universality and complexity. Degrees of relative complexity in terms of similarity from a correlation matrix have been obtained. The results show that the architecture of a Universal Fuzzy Property Grammar is flexible, reusable, and re-trainable, and it can easily take into account new sets of languages, perfecting the degree of universality and complexity of the linguistic constraints as well as the degree of complexity between languages.

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Section: Fuzzy Natural Logic Computing Universals and Linguistic Comp...mentioning

confidence: 99%

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confidence: 99%

A Fuzzy Grammar for Evaluating Universality and Complexity in Natural Language

et al. 2022

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“…Some of the works in linguistics integrating FNL as a fundamental part of their framework can be found in the modelling of a Fuzzy Property Grammar [17][18][19][20]. FNL is essential to define the basis of a fuzzy grammar with linguistic features in such work.…”

Section: Introductionmentioning

confidence: 99%

“…All the linguistic descriptions from now on are conducted following the framework of Fuzzy Property Grammars (FPGr). For a deeper insight of the theory, see [18][19][20].…”

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Describing Linguistic Vagueness of Evaluative Expressions Using Fuzzy Natural Logic and Linguistic Constraints

2022

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In recent years, the study of evaluative linguistic expressions has crossed the field of theoretical linguistics and has aroused interest in very different research areas such as artificial intelligence, psychology or cognitive linguistics. The interest in this type of expressions may be due to its relevance in applications such as opinion mining or sentiment analysis. This paper brings together Fuzzy Natural Logic and Fuzzy Property Grammars to approach evaluative expressions. Our contribution includes the marriage of mathematical and linguistic methods for providing a formalism to deal with the linguistic vagueness of evaluative expressions by describing the syntax and semantics of these structures. We contribute to the study of evaluative linguistic expressions by proposing a formal characterization of them where the concepts of semantic prime, borderline evaluative expressions and markedness are defined and where the relation between the semantic constraints of evaluations and their sentiment can be established. A proof-of-concept of how to create a lexicon of evaluative expressions for future computational applications is presented. The results demonstrate that linguistic evaluative expressions are gradient, have sentiment, and that the evaluations work as a relation of hypernym and hyponym, the hypernym being a semantic prime. Our findings provide the basis for building an ontology of evaluative expressions for future computational applications.

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Automate Descriptive Answer Grading using Reference based Models

Sayeed

Gupta

2022

2022 OITS International Conference on Information Technology (OCIT)

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A Fuzzy Approach to Language Universals for NLP

Cited by 3 publications

References 16 publications

A Fuzzy Grammar for Evaluating Universality and Complexity in Natural Language

A Fuzzy Grammar for Evaluating Universality and Complexity in Natural Language

Describing Linguistic Vagueness of Evaluative Expressions Using Fuzzy Natural Logic and Linguistic Constraints

Automate Descriptive Answer Grading using Reference based Models

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