Abstract Syntax as Interlingua: Scaling Up the Grammatical Framework from Controlled Languages to Robust Pipelines

syntax is an interlingual representation used in compilers. Grammatical Framework (GF) applies the abstract syntax idea to natural languages. The development of GF started in 1998, first as a tool for controlled language implementations, where it has gained an established position in both academic and commercial projects. GF provides grammar resources for over 40 languages, enabling accurate generation and translation, as well as grammar engineering tools and components for mobile and Web applications. On the research side, the focus in the last ten years has been on scaling up GF to wide-coverage language processing. The concept of abstract syntax offers a unified view on many other approaches: Universal Dependencies, WordNets, FrameNets, Construction Grammars, and Abstract Meaning Representations. This makes it possible for GF to utilize data from the other approaches and to build robust pipelines. In return, GF can contribute to data-driven approaches by methods to transfer resources from one language to others, to augment data by rule-based generation, to check the consistency of hand-annotated corpora, and to pipe analyses into high-precision semantic back ends. This article gives an overview of the use of abstract syntax as interlingua through both established and emerging NLP applications involving GF.

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

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.

Data Management in NTA Structures

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.

Sublanguages and Controlled Languages

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.