A Survey of Uses of GATE (original) (raw)

Experience of using GATE for NLP R&D

2000

GATE, a General Architecture for Text Engineering, aims to provide a software infrastructure for researchers and developers working in NLP. GATE has now been widely available for four years. In this paper we review the objectives which motivated the creation of GATE and the functionality and design of the current system. We discuss the strengths and weaknesses of the current system, identify areas for improvement.

GATE-a General Architecture for Text Engineering

1996

Much progress has been made in the provision of reusable data resources for Natural Language Engineering, such as grammars, lexicons, thesauruses. Although a number of projects have addressed the provision of reusable algorithmic resources (or 'tools'), takeup of these resources has been relatively slow. This paper describes GATE, a General Architecture for Text Engineering, which is a freely-available system designed to help alleviate the problem.

Using GATE as an environment for teaching NLP

Proceedings of the ACL-02 Workshop on Effective tools and methodologies for teaching natural language processing and computational linguistics -, 2002

In this paper we argue that the GATE architecture and visual development environment can be used as an effective tool for teaching language engineering and computational linguistics. Since GATE comes with a customisable and extendable set of components, it allows students to get hands-on experience with building NLP applications. GATE also has tools for corpus annotation and performance evaluation, so students can go through the entire application development process within its graphical development environment.

Software Infrastructure for Natural Language Processing

Computing Research Repository, 1997

We classify and review current approaches to software infrastructure for research, development and delivery of NLP systems. The task is motivated by a discussion of current trends in the field of NLP and Language Engineering. We describe a system called GATE (a General Architecture for Text Engineering) that provides a software infrastructure on top of which heterogeneous NLP processing modules may be evaluated and refined individually, or may be combined into larger application systems. GATE aims to support both researchers and developers working on component technologies (e.g. parsing, tagging, morphological analysis) and those working on developing end-user applications (e.g. information extraction, text summarisation, document generation, machine translation, and second language learning). GATE promotes reuse of component technology, permits specialisation and collaboration in large-scale projects, and allows for the comparison and evaluation of alternative technologies. The first release of GATE is now available.

Current issues in software engineering for natural language processing

2003

In Natural Language Processing (NLP), research results from software engineering and software technology have often been neglected. This paper describes some factors that add complexity to the task of engineering reusable NLP systems (beyond conventional software systems). Current work in the area of design patterns and composition languages is described and claimed relevant for natural language processing. The benefits of NLP componentware and barriers to reuse are outlined, and the dichotomies "system versus experiment" and "toolkit versus framework" are discussed. It is argued that in order to live up to its name language engineering must not neglect component quality and architectural evaluation when reporting new NLP research.

Evolving GATE to meet new challenges in language engineering

Natural Language Engineering, 2004

In this paper we present recent work on GATE, a widely-used framework and graphical development environment for creating and deploying Language Engineering components and resources in a robust fashion. The GATE architecture has facilitated the development of a number of successful applications for various language processing tasks (such as Information Extraction, dialogue and summarisation), the building and annotation of corpora and the quantitative evaluations of LE applications. The focus of this paper is on recent developments in response to new challenges in Language Engineering: Semantic Web, integration with Information Retrieval and data mining, and the need for machine learning support.

Evolving GATE to Meet New Challenges in Language Engineeringy

Natural Language Engineering, 2004

In this paper we present recent work on GATE, a widely-used framework and graphical development environment for creating and deploying Language Engineering components and resources in a robust fashion. The GATE architecture has facilitated the development of a number of successful applications for various language processing tasks (such as Information Extraction, dialogue and summarisation), the building and annotation of corpora and the quantitative evaluations of LE applications. The focus of this paper is on recent developments in response to new challenges in Language Engineering: Semantic Web, integration with Information Retrieval and data mining, and the need for machine learning support.