Bridging the gaps: interoperability for language engineering architectures using GrAF

Ide, Nancy; Suderman, Keith

doi:10.1007/s10579-011-9175-7

Cited by 10 publications

(11 citation statements)

References 7 publications

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“…GATE and UIMA are complementary, and we have developed an interoperation layer that will run UIMA-based applications within GATE and vice-versa. An interoperation mechanism based on the GrAF format [23] is also available.…”

Section: Design and Implementationmentioning

confidence: 99%

Getting More Out of Biomedical Documents with GATE's Full Lifecycle Open Source Text Analytics

et al. 2013

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This software article describes the GATE family of open source text analysis tools and processes. GATE is one of the most widely used systems of its type with yearly download rates of tens of thousands and many active users in both academic and industrial contexts. In this paper we report three examples of GATE-based systems operating in the life sciences and in medicine. First, in genome-wide association studies which have contributed to discovery of a head and neck cancer mutation association. Second, medical records analysis which has significantly increased the statistical power of treatment/outcome models in the UK's largest psychiatric patient cohort. Third, richer constructs in drug-related searching. We also explore the ways in which the GATE family supports the various stages of the lifecycle present in our examples. We conclude that the deployment of text mining for document abstraction or rich search and navigation is best thought of as a process, and that with the right computational tools and data collection strategies this process can be made defined and repeatable. The GATE research programme is now 20 years old and has grown from its roots as a specialist development tool for text processing to become a rather comprehensive ecosystem, bringing together software developers, language engineers and research staff from diverse fields. GATE now has a strong claim to cover a uniquely wide range of the lifecycle of text analysis systems. It forms a focal point for the integration and reuse of advances that have been made by many people (the majority outside of the authors' own group) who work in text processing for biomedicine and other areas. GATE is available online <1> under GNU open source licences and runs on all major operating systems. Support is available from an active user and developer community and also on a commercial basis.

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Section: Design and Implementationmentioning

confidence: 99%

Getting More Out of Biomedical Documents with GATE's Full Lifecycle Open Source Text Analytics

et al. 2013

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“…Differences in theoretical insights and assumptions make standardization challenging. Recent efforts therefore mainly aim for interoperability among formats (Ide and Suderman, 2012). In this section, we will describe several formats that serve this purpose.…”

Section: Related Workmentioning

confidence: 99%

“…Because nodes can only point to locations in the text and not to other annotations, the annotation does not form a true graph. It is difficult to represent hierarchical annotations (Ide and Suderman, 2012) making it less suitable for our purposes. The Unstructured Information Management Architecture (Ferrucci and Lally, 2004, UIMA) provides data representations and interfaces that are platform independent.…”

Section: Linguistic Annotationsmentioning

confidence: 99%

Shallow features as indicators of English–German contrasts in lexical cohesion

Kunz

Lapshinova-Koltunski

Martínez

et al. 2017

LiC

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This paper contrasts lexical cohesion between English and German spoken and written registers, reporting findings from a quantitative lexical analysis. After an overview of research aims and motivations we formulate hypotheses on distributions of shallow features as indicators of lexical cohesion across languages and modes and with respect to register ranking and variation. The shallow features analysed are: highly frequent words in texts, lexical density, standardized type-token-ratio, top-frequent content words of the language within individual registers and texts, and several types of Latinate words. Descriptive analyses of the corpus are then presented and statistically validated with the help of univariate and multivariate analyses. The results are interpreted relative to our hypotheses and related to the following properties of texts in terms of lexical cohesion: semantic variability, cohesive strength, number and length of nominal chains, degree of specification of lexis, and degree of variation along all of these properties.

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“…In [9], the Graph Annotation Framework (GrAF) was used to bridge the models of UIMA and GATE. GrAF is the XML serialization of the Linguistic Annotation Framework (LAF) and has recently been standardized by ISO.…”

Section: Qualitative Comparison With Other Framework and Formatsmentioning

confidence: 99%

Integrating NLP Using Linked Data

Hellmann

Lehmann

Auer

et al. 2013

Lecture Notes in Computer Science

137

106

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We are currently observing a plethora of Natural Language Processing tools and services being made available. Each of the tools and services has its particular strengths and weaknesses, but exploiting the strengths and synergistically combining different tools is currently an extremely cumbersome and time consuming task. Also, once a particular set of tools is integrated, this integration is not reusable by others. We argue that simplifying the interoperability of different NLP tools performing similar but also complementary tasks will facilitate the comparability of results and the creation of sophisticated NLP applications. In this paper, we present the NLP Interchange Format (NIF). NIF is based on a Linked Data enabled URI scheme for identifying elements in (hyper-)texts and an ontology for describing common NLP terms and concepts. In contrast to more centralized solutions such as UIMA and GATE, NIF enables the creation of heterogeneous, distributed and loosely coupled NLP applications, which use the Web as an integration platform. We present several use cases of the second version of the NIF specification (NIF 2.0) and the result of a developer study.

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Bridging the gaps: interoperability for language engineering architectures using GrAF

Cited by 10 publications

References 7 publications

Getting More Out of Biomedical Documents with GATE's Full Lifecycle Open Source Text Analytics

Getting More Out of Biomedical Documents with GATE's Full Lifecycle Open Source Text Analytics

Shallow features as indicators of English–German contrasts in lexical cohesion

Integrating NLP Using Linked Data

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