Parsing SBVR-Based Controlled Languages

This article deals with the topic of sublanguage, the original language grammar subset, which informs various text outputs. Despite routine deviance from standard languages, quite often sublanguage grammatical patterns draw heavily from standard languages. Machine translation, database extraction from texts, and natural language generation are some ways of sublanguage processing. The definition of controlled language projects the difference between itself and sublangauge. The former is described as a restricted set of natural language, engineered to facilitate communication between expert native speakers and either non-expert natives or expert non-natives. However, the difference lies in the fact that controlled language is not a natural subset, unlike sublangauge. Unlike sublanguage that works like a general language in not restricting its sentences, controlled language sets an upper limit, typically around twenty-five. Contrast between controlled language and sublanguage assumes theoretical importance.

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Implementing Controlled Languages in GF

Lecture Notes in Computer Science - Controlled Natural Language ◽

10.1007/978-3-642-14418-9_6 ◽

2010 ◽

pp. 82-101 ◽

Cited By ~ 17

Author(s):

Krasimir Angelov ◽

Aarne Ranta

Keyword(s):

Controlled Languages

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THE EVIDENCE-BASED MEDICINE PICO STRATEGY APPLIED TO DENTISTRY USING MESH, EMTREE AND DECS

Revista Facultad de Odontología ◽

10.17533/udea.rfo.v31n1-2a8 ◽

2019 ◽

Vol 31 (1-2) ◽

Author(s):

María Teresa Alarcón Gil ◽

Sonia Osorio Toro ◽

Gloria Patricia Baena Caldas

Keyword(s):

Evidence Based Medicine ◽

Research Question ◽

Scientific Information ◽

Bibliographic Databases ◽

Evidence Based ◽

Structure Search ◽

Research Questions ◽

The Right ◽

Based Medicine ◽

Controlled Languages

Introduction: the PICO mnemonic is an evidence-based medicine tool that helps formulate the research questions needed to conduct the right search for scientific information. To properly classify this information, controlled languages or thesauruses are used for information retrieval. The aim was to identify whether the PICO search strategy in evidence-based medicine using the MeSH, Emtree and DeCS thesauruses answers a research question in the field of dentistry. Methods: to carry out the PICO strategy, a research question was formulated, identifying the natural language terms for each component of the PICO acronym, which were normalized into the three thesauruses to create the search equations. Results: 43 results were foundon Medline through PubMed, 5 on Embase, and 0 on LILACS. There were 4 original articles that answer the research question, proving to be an effective strategy for finding clinical evidence. Conclusion: this study shows that the strategy helps obtain results to answer the question posed. It should be noted that, in order to successfully search and retrieve information, researchers should use the PICO strategy and get familiar with the thesauruses that help structure search equations in the various bibliographic databases.

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Data Management in NTA Structures

N-ary Relations for Logical Analysis of Data and Knowledge - Advances in Knowledge Acquisition, Transfer, and Management ◽

10.4018/978-1-5225-2782-4.ch007 ◽

2018 ◽

pp. 236-256

Keyword(s):

Data Management ◽

Search Engines ◽

Relational Algebra ◽

Algebraic Models ◽

Knowledge Processing ◽

Question And Answer ◽

Controlled Languages

As for making databases more intelligent, NTA can be considered an extension of relational algebra to knowledge processing. Besides, we propose an approach to development of search engines, in particular, question-and-answer teaching systems based on controlled languages and algebraic models for representation and processing of question-and-answer texts.

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Sublanguages and Controlled Languages

The Oxford Handbook of Computational Linguistics 2nd edition ◽

10.1093/oxfordhb/9780199573691.013.015 ◽

2016 ◽

Cited By ~ 1

Author(s):

Richard I. Kittredge

Keyword(s):

Language Processing ◽

Subject Matter ◽

Automatic Processing ◽

Naturally Occurring ◽

First Case ◽

Important Notion ◽

Controlled Languages ◽

Language Meaning ◽

Controlled Language

Restricted subsystems of language can arise spontaneously in a subject-matter domain where speech or writing is used for special purposes. Alternatively, language restrictions can be imposed by conscious design. This chapter introduces the phenomenon of natural sublanguage in the first case, and contrasts it with the increasingly important notion of controlled language, which applies in the second case. Many of the successful language processing applications which deal with language meaning are limited to naturally occurring sublanguages. We give examples of natural sublanguages and describe their key properties for automatic processing. One or more related sublanguages may serve as the basis for a controlled language, where standards are introduced to reduce ambiguity, limit complexity, and enforce uniform style.

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