scholarly journals Designing the Lexical Rules for the Parsing of ASD-STE100 Function Words in ARTEMIS from a Role and Reference Grammar Perspective

2019 ◽  
Vol 17 ◽  
pp. 149
Author(s):  
María del Carmen Fumero-Pérez ◽  
Ana Díaz-Galán
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Semantic Representation ◽  
Technical Documentation ◽  
Simple Sentence ◽  
Function Words ◽  
Role And Reference Grammar ◽  
Reference Grammar ◽  
Lexical Rules ◽  
Controlled Language

ARTEMIS (Automatically Representing Text Meaning via an Interlingua-based System), is a natural language processing device, whose ultimate aim is to be able to understand natural language fragments and arrive at their syntactic and semantic representation. Linguistically, this parser is founded on two solid linguistic theories: the Lexical Constructional Model and Role and Reference Grammar. Although the rich semantic representations and the multilingual character of Role and Reference Grammar make it suitable for natural language understanding tasks, some changes to the model have proved necessary in order to adapt it to the functioning of the ARTEMIS parser. This paper will deal with one of the major modifications that Role and Reference Grammar had to undergo in this process of adaptation, namely, the substitution of the operator projection for feature-based structures, and how this will influence the description of function words in ARTEMIS, since they are strongly responsible for the encoding of the grammatical information which in Role and Reference Grammar is included in the operators. Currently, ARTEMIS is being implemented for the controlled natural language ASD-STE100, the Aerospace and Defence Industries Association of Europe Simplified Technical English, which is an international specification for the preparation of technical documentation in a controlled language. This controlled language is used in the belief that its simplified nature makes it a good corpus to carry out a preliminary testing of the adequacy of the parser. In this line, the aim of this work is to create a catalogue of function words in ARTEMIS for ASD-STE100, and to design the lexical rules necessary to parse the simple sentence and the referential phrase in this controlled language.

scholarly journals Automatically Representing TExt Meaning via an Interlingua-based System (ARTEMIS). A further step towards the computational representation of RRG

2017 ◽  
Vol 1 (1) ◽  
pp. 61 ◽  
Author(s):  
Ricardo Mairal-Usón ◽  
Francisco Cortés-Rodríguez
Keyword(s):  
Language Processing ◽  
Semantic Representation ◽  
Analysis Data ◽  
Logical Structure ◽  
Automatic Generation ◽  
Role And Reference Grammar ◽  
Reference Grammar ◽  
Level 1 ◽  
Computational Resources ◽  
Computational Representation

Within the framework of FUNK Lab – a virtual laboratory for natural language processing inspired on a functionally-oriented linguistic theory like Role and Reference Grammar-, a number of computational resources have been built dealing with different aspects of language and with an application in different scientific domains, i.e. terminology, lexicography, sentiment analysis, document classification, text analysis, data mining etc. One of these resources is ARTEMIS (<span style="text-decoration: underline;">A</span>utomatically <span style="text-decoration: underline;">R</span>epresenting <span style="text-decoration: underline;">TE</span>xt <span style="text-decoration: underline;">M</span>eaning via an <span style="text-decoration: underline;">I</span>nterlingua-Based <span style="text-decoration: underline;">S</span>ystem), which departs from the pioneering work of Periñán-Pascual (2013) and Periñán-Pascual &amp; Arcas (2014).  This computational tool is a proof of concept prototype which allows the automatic generation of a conceptual logical structure (CLS) (cf. Mairal-Usón, Periñán-Pascual and Pérez 2012; Van Valin and Mairal-Usón 2014), that is, a fully specified semantic representation of an input text on the basis of a reduced sample of sentences. The primary aim of this paper is to develop the syntactic rules that form part of the computational grammar for the representation of simple clauses in English. More specifically, this work focuses on the format of those syntactic rules that account for the upper levels of the RRG Layered Structure of the Clause (LSC), that is, the <em>core</em> (and the level-1 construction associated with it), the <em>clause</em> and the <em>sentence </em>(Van Valin 2005). In essence, this analysis, together with that in Cortés-Rodríguez and Mairal-Usón (2016), offers an almost complete description of the computational grammar behind the LSC for simple clauses.

Constructional meaning representation within a knowledge engineering framework

2015 ◽  
Vol 13 (1) ◽  
pp. 1-27
Author(s):  
Ricardo Mairal-Usón
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Conceptual Knowledge ◽  
Knowledge Engineering ◽  
Meaning Construction ◽  
Engineering Project ◽  
Language Understanding ◽  
Role And Reference Grammar ◽  
Reference Grammar ◽  
Meaning Representation

FunGramKB is a multipurpose lexico-conceptual knowledge base for natural language processing systems, and more particularly, for natural language understanding. The linguistic layer of this knowledge-engineering project is grounded in compatible aspects of two linguistic accounts, namely, Role and Reference Grammar (RRG) and the Lexical Constructional Model (LCM). RRG, although originally a lexicalist approach, has recently incorporated constructional configurations into its descriptive and explanatory apparatus. The LCM has sought to understand from its inception the factors that constrain lexical-constructional integration. Within this theoretical context, this paper discusses the format of lexical entries, highly inspired in RRG proposals, and of constructional schemata, which are organized according to the descriptive levels supplied by the LCM. Both lexical and constructional structure is represented by means of Attribute Value Matrices (AVMs). Thus, the lexical and grammatical levels of FunGramKB are the focus of our attention here. Additionally, the need for a conceptualist approach to meaning construction is highlighted throughout our discussion.

scholarly journals The interrelation of semantic structure and syntactic variation in Old English verb classes: catalogue of syntactico-semantic constructions

2005 ◽  
pp. 111 ◽  
Author(s):  
Marta González Orta
Keyword(s):  
Old English ◽  
Semantic Representation ◽  
Semantic Structure ◽  
Syntactic Variation ◽  
Verb Classes ◽  
Lexical Representations ◽  
Role And Reference Grammar ◽  
Reference Grammar ◽  
Lexical Rules ◽  
Core Meaning

The aim of this paper is to motivate the syntactic and morphological behaviour of the Old English verbs which share the core meaning of 'to remember', 'to emit a smell', 'to produce a sound' and 'to speak' from their semantic structure. Firstly, as a result of the analysis of these verb subclasses, I will propose a subclass-based lexical template for each lexical subclass. Within the Lexical Grammar Model, lexical templates are conceived as lexical representations where meaning description is encapsulated and interacts with the syntactic behaviour of lexical units. In order to construct a lexical template, Role and Reference Grammar logical structures will be complemented by a semantic decomposition which will define different lexical (sub-)classes. Secondly, the Lexical Template Modelling Process will stipulate the linking between the syntactic and semantic representation of these verbs. This process will establish the lexical rules that account for the mapping between the different semantic constructions and the syntactic structures and alternations in which these verbs participate and the lexical templates codified by these verb subclasses. As a result, a catalogue of the syntactico-semantic constructions exhibited by these Old English verbal predicates will be provided.

Reusing a syntactic generator for CALL purposes

ReCALL ◽  
2000 ◽  
Vol 12 (1) ◽  
pp. 79-91 ◽  
Author(s):  
ANNE VANDEVENTER ◽  
MARIE-JOSÉE HAMEL
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Deep Structure ◽  
Semantic Representation ◽  
Generation Process ◽  
Generation System ◽  
Sentence Generation ◽  
Advantages And Disadvantages ◽  
Grammatical Sentence

This article presents briefly the advantages and disadvantages of reusing natural language processing (NLP) tools in the CALL context. The issue is addressed through the description of GBGen, a sentence generation system. The abstract semantic representation used as input for the generator is described, as well as the actual generation process, from a deep structure to a grammatical sentence through transformations and the application of morphology. The possible didactic value of such a tool is then evaluated and the outline of a CALL scenario given. Finally, proposed adaptations of the generator for the CALL context are discussed.

Aspectual features in Role and Reference Grammar

2014 ◽  
Vol 27 (1) ◽  
pp. 23-53 ◽  
Author(s):  
Francisco J. Cortés Rodriguez
Keyword(s):  
Semantic Representation ◽  
Functional Model ◽  
Morphological Aspect ◽  
Functional Projection ◽  
Role And Reference Grammar ◽  
The Core ◽  
Reference Grammar ◽  
Event Structures

The kernel of the semantic representation of a predicate in Role and Reference Grammar (RRG) is based on its characterization in terms of an Aktionsart typology based on Vendler’s (1957) classes plus some additional elements from Smith (1997) and Dowty (1979). This means that event structures are mainly considered a lexical phenomenon pertaining to predicates, and only occasionally higher predicational structures are considered in event construction. Even though this approach is adequate to a great extent, there are still some problems in the approach taken in RRG. The most significant drawback is that non-lexical aspects appear intermingled with predicate-only features, which leads to misinterpretations and misclassifications of predicates. Consequently, it sees more sensible to bring a functional model of grammar like RRG to a compromise position and, thus, consider in what ways different units identified as belonging to the different layers in RRG’s syntactic projections ‘conspire’ in the final aspectual characterization of events. In this line, this paper will propose a classification of aspectual features in terms of the levels found in the functional projection of the clause as devised in RRG, namely the Predicate Level (the domain of Aktionsart typology), the Nucleus (where morphological aspect has scope) and the Core (the locus for what will be described as ‘aspectuality’ features).

scholarly journals Introducing Computational Semantics for Natural Language Understanding in Conversational Nutrition Coaches for Healthy Eating

Proceedings ◽  
2018 ◽  
Vol 2 (19) ◽  
pp. 506
Author(s):  
Antonio Benítez-Guijarro ◽  
Zoraida Callejas ◽  
Manuel Noguera ◽  
Kawtar Benghazi
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Healthy Eating ◽  
User Interfaces ◽  
Eating Habits ◽  
Semantic Representation ◽  
Natural Language Understanding ◽  
Computational Semantics ◽  
Language Understanding ◽  
Healthy Eating Habits

Nutrition e-coaches have demonstrated to be a successful tool to foster healthy eating habits, most of these systems are based on graphical user interfaces where users select the meals they have ingested from predefined lists and receive feedback on their diet. On one side the use of conversational interfaces based on natural language processing allows users to interact with the coach more easily and with fewer restrictions. However, on the other side natural language introduces more ambiguity, as instead of selecting the input from a predefined finite list of meals, the user can describe the ingests in many different ways that must be translated by the system into a tractable semantic representation from which to derive the nutritional aspects of interest. In this paper, we present a method that improves state-of-the-art approaches by means of the inclusion of nutritional semantic aspects at different stages during the natural language understanding processing of the user written or spoken input. The outcome generated is a rich nutritional interpretation of each user ingest that is independent of the modality used to interact with the coach.

Semantic Representation for Understanding Meaning Based on Correspondence Between Meanings

2006 ◽  
Vol 10 (6) ◽  
pp. 876-912
Author(s):  
Akira Takagi ◽  
◽  
Hideki Asoh ◽  
Yukihiro Itoh ◽  
Makoto Kondo ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Semantic Representation ◽  
Semantic Content ◽  
Semantic Interpretation ◽  
Basic Unit ◽  
Dependency Relation ◽  
Dependency Structures ◽  
Attribute Value

One of the biggest problems in natural language processing is that its processing target (i.e. the surface expressions of sentences) has a great deal of diversity. In order to reduce the difficulty, it is desirable to extract the semantic content denoted by a sentence in such a way that it does not depend on the surface expressions as much as possible. This paper proposes a new semantic representation and general interpretive procedures that enable us to obtain the result of semantic interpretation from a variety of surface expressions of the input independently of their dependency structures. In the semantic representation to be proposed, a variety of surface dependency relations are compressed into attribute nouns, and the meaning expressed by dependency relation is represented in a uniform style (i.e. attribute = value). This approach enables us to establish correspondence between meanings by using the attribute-value pair as a basic unit. With this semantic representation and the general interpretive procedures, the same interpretive result can be obtained from sentences with different dependency structures. We will further demonstrate that semantic contents of multiple sentences can be integrated by interpreting them based on the correspondence between meanings.

scholarly journals AN OVERVIEW OF AUTOMATED TRANSLATION AND ITS LINGUISTIC PROBLEMS

2021 ◽  
pp. 139-149
Keyword(s):  
Natural Language ◽  
Machine Translation ◽  
Computational Linguistics ◽  
Language Processing ◽  
Information Exchange ◽  
Rapid Development ◽  
Language Translation ◽  
Target Language ◽  
Technical Documentation ◽  
Automated Translation

Language, as the information carrier, has become the most significant means for humans to communicate. However, it has been considered as the barrier of communications between people from different countries. The problem of converting a language quickly and efficiently has become a problem of common concern for humanity. In fact, the demand for language translation has greatly increased in recent times due to effect of cross-regional communication and the need for information exchange. Most material needs to be translated, including scientific and technical documentation, instruction manuals, legal documents, textbooks, publicity leaflets, newspaper reports, etc. The issue is challenging and difficult but mostly it is tedious and repetitive and requires consistency and accuracy. It is becoming difficult for professional translators to meet the increasing demands of translation. In such a situation, the machine translation can be used as a substitute. Machine Translation is the process of converting a natural source language into another natural target language by computer. It is a branch of natural language processing and it has a close relationship with computational linguistics and natural language understanding. With the rapid development of the Internet and the integration of the world economy, how to overcome the barrier of language has become a common problem of the international community. This paper offers an overview of Machine Translation (MT) including the history of MT, linguistic problems of MT, the problem of multiple meanings in MT, syntactic transformations in MT, translation of phraseological combinations in MT systems.

scholarly journals Conceptualización de entidades terminológicas en una subontología de derecho penal: análisis del concepto superordinado +DRUG_00 en FunGramKb

2020 ◽  
Vol 15 (1) ◽  
pp. 15
Author(s):  
Ángel M. Felices Lago ◽  
Pedro Ureña Gómez-Moreno
Keyword(s):  
Natural Language ◽  
Knowledge Base ◽  
Conceptual Knowledge ◽  
Role And Reference Grammar ◽  
The Core ◽  
Reference Grammar ◽  
Stepwise Method ◽  
Core Ontology ◽  
Derecho Penal

<p>This article describes some phases in the process of constructing a term-based Satellite Ontology within the architecture of the Core Ontology integrated in FunGramKB (a lexico-conceptual knowledge base for the computational processing of natural language). The semantic decomposition of complex terminology is implemented following the COHERENT methodology (a stepwise method for formalizing specialized concepts). For that purpose, we have selected the superordinate concept +DRUG_00 as well as other subordinate concepts in the domain of drugs such as $METHAMPHETAMINE_00, $CANNABIS_00, and $COCAINE_00. The definitions of the concepts selected for the study are based on COREL, an interface metalanguage inspired on some general principles of Role and Reference Grammar (RRG). As a result of the modeling, subsumption and hierarchization process the top conceptual path is represented in the Satellite Ontology as follows: #ENTITY &gt; #PHYSICAL &gt; #OBJECT &gt; SELF_CONNECTED_OBJECT &gt; +ARTIFICIAL_OBJECT_00 &gt; +SUBSTANCE_00 &gt; +SOLID_00&gt; +DRUG_00.</p>

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