Linguistic processor of the integrated system for solving planimetric problems

2021 ◽  
Vol 25 (2) ◽  
pp. 185-193
Author(s):  
Sergeyi S. Kurbatov
Keyword(s):  
Experimental Study ◽  
Natural Language ◽  
Syntactic Structure ◽  
Semantic Representation ◽  
Interactive Visualization ◽  
Integrated System ◽  
Regular Expressions ◽  
Language Description

The paper deals with the original algorithms of the linguistic processor of the integrated system for solving planimetric problems. The algorithms successfully combine the method of synonymic transformations with the extended method of regular expressions processing. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. Linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. The results of the experimental study of the linguistic processor are interpreted. The direction of further research related to the development of the proposed approach is outlined.

scholarly journals Linguistic processor integration for solving planimetric problems

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Natural Language ◽  
Syntactic Structure ◽  
Semantic Representation ◽  
Interactive Visualization ◽  
Subject Area ◽  
Syntactic Structures ◽  
The Subject ◽  
Language Description

The research deals with the original algorithms of the linguistic processor integration for solving planimetric problems. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. The linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. During the experiments, several dozens of standard syntactic structures correctly displayed in the semantic structures of the subject area were obtained. The direction of further research related to the development of the proposed approach is outlined.

scholarly journals Linguistic Processor Integration for Solving Planimetric Problems

2021 ◽  
Vol 15 (4) ◽  
pp. 1-14
Author(s):  
Sergeyi S. Kurbatov
Keyword(s):  
Natural Language ◽  
Syntactic Structure ◽  
Semantic Representation ◽  
Interactive Visualization ◽  
Subject Area ◽  
Syntactic Structures ◽  
The Subject ◽  
Language Description

The research deals with the original algorithms of the linguistic processor integration for solving planimetric problems. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. The linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. During the experiments, several dozens of standard syntactic structures correctly displayed in the semantic structures of the subject area were obtained. The direction of further research related to the development of the proposed approach is outlined.

The indivisibility of words

1979 ◽  
Vol 15 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Geoffrey Sampson
Keyword(s):  
Natural Language ◽  
Syntactic Structure ◽  
Semantic Representation ◽  
Tree Structure ◽  
Breaking Point ◽  
Derivational Morphology ◽  
Adequate Description ◽  
Linguistic Representation ◽  
Level I

Many contemporary linguists hold that an adequate description of a natural language must represent many of its vocabulary items as syntactically and/or semantically complex. A sentence containing the word kill, for instance, will on this view be assigned a ‘deep syntactic structure’ or ‘semantic representation’ in which kill is represented by a portion or portions of tree-structure, the lowest nodes of which are labelled with ‘semantic primitives’ such as CAUSE and DIE, or CAUSE, BECOME, NOT and ALIVE. In the case of words such as cats or walked, which are formed in accordance with productive rules of ‘inflexional’ rather than ‘derivational’ morphology, there is little dispute that their composite status will be reflected at most or all levels of linguistic representation. (That is why I refer, above, to ‘vocabulary items’: cat and cats may be called different ‘words’, but not different elements of the English vocbulary.) When morphologically simple words such as kill are treated as composite at a ‘deeper’ level, I, for one, find my credulity strained to breaking point. (The case of words formed in accordance with productive or non-productive rules of derivational morphology, such as killer or kingly, is an intermediate one and I shall briefly return to it below.)

The Linguistic Expression of a Semantic Relation

1998 ◽  
Vol 12 ◽  
pp. 175-188
Author(s):  
Sophie Aslanides
Keyword(s):  
Natural Language ◽  
Syntactic Structure ◽  
Semantic Representation ◽  
Semantic Relation ◽  
Linguistic Knowledge ◽  
Linguistic Expression ◽  
Generation System ◽  
Language Generation ◽  
Linguistic Databases ◽  
Linguistic Means

Abstract. This article sets out some of the results of wider research on the linguistic databases of a natural language generation system. One of the necessary steps in the building of such databases is to determine the linguistic means the generator must have in order to produce a linguistic form that corresponds to the semantic representation given as an input. We wish to focus here on the theoretical choices and issues rather than on the application itself. We assume that texts have a syntactic structure, whose characteristics are partly comparable to the syntactic structure of a sentence, and that a connective can be considered as a textual predicate which has arguments that are constrained in the same way as the arguments of a verb. This article will concentrate more specifically on one particular semantic relation — the simultaneity of two events — and will show how the taxonomy of the associated connectives can be elaborated. Finally, we will set out some of the major developments of this research, which concern the interface between conceptual and linguistic knowledge.

scholarly journals On Learning Interpreted Languages with Recurrent Models

2022 ◽  
pp. 1-13
Author(s):  
Denis Paperno
Keyword(s):  
Natural Language ◽  
Data Processing ◽  
Syntactic Structure ◽  
Neural Nets ◽  
Training Data ◽  
Sequential Data ◽  
Extensive Training ◽  
Formal Syntax ◽  
Compositional Interpretation

Abstract Can recurrent neural nets, inspired by human sequential data processing, learn to understand language? We construct simplified datasets reflecting core properties of natural language as modeled in formal syntax and semantics: recursive syntactic structure and compositionality. We find LSTM and GRU networks to generalise to compositional interpretation well, but only in the most favorable learning settings, with a well-paced curriculum, extensive training data, and left-to-right (but not right-to-left) composition.

scholarly journals The Ka- Passive Form in Balinese

2019 ◽  
Vol 10 (4) ◽  
pp. 886
Author(s):  
Nyoman Sujaya ◽  
Ketut Artawa ◽  
I Nyoman Kardana ◽  
Made Sri Satyawati
Keyword(s):  
Syntactic Structure ◽  
Semantic Representation ◽  
Narrative Texts ◽  
Passive Voice ◽  
Base Form ◽  
The Voice

This paper accounts for the ka- passive form in Balinese. It focuses on its syntactic and semantic representation. Using the data taken from Balinese narrative texts issued in the Bali Orti of Bali Post newspaper, and applying the RRG theory by Van Valin and Randy (1999), it was found out that the ka- passive belongs to a morphological passive voice of Balinese where the the voice is marked on the verb (it is marked by prefix ka-). The ka- base form can be attached by applicative suffixes such as -ang, -in, and –an. These morphological verbs imply various syntactic structure and semantic representation.

scholarly journals Natural language description of images using hybrid recurrent neural network

2019 ◽  
Vol 9 (4) ◽  
pp. 2932
Author(s):  
Md. Asifuzzaman Jishan ◽  
Khan Raqib Mahmud ◽  
Abul Kalam Al Azad
Keyword(s):  
Neural Network ◽  
Natural Language ◽  
Recurrent Neural Network ◽  
Short Term Memory ◽  
Text Line ◽  
Short Term ◽  
Word Representation ◽  
Benchmark Datasets ◽  
Long Short Term Memory ◽  
Language Description

We presented a learning model that generated natural language description of images. The model utilized the connections between natural language and visual data by produced text line based contents from a given image. Our Hybrid Recurrent Neural Network model is based on the intricacies of Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bi-directional Recurrent Neural Network (BRNN) models. We conducted experiments on three benchmark datasets, e.g., Flickr8K, Flickr30K, and MS COCO. Our hybrid model utilized LSTM model to encode text line or sentences independent of the object location and BRNN for word representation, this reduced the computational complexities without compromising the accuracy of the descriptor. The model produced better accuracy in retrieving natural language based description on the dataset.

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