GATE, a General Architecture for Text Engineering Hamish Cunningham Department of Computer Science, University of Sheffield ENST, Paris, 20/1/2003 Natural Language Engineering in Sheffield: One of the largest Human Language Technology groups in the EU 50 staff in Language and Speech Processing; 25 in Information Retrieval, including 6 professors A focus on scientific method in AI (participate in all the leading quantitative evaluation programmes in the US) A focus on engineering high-quality open-source software for applications and demonstrators

2(27) GATE, a General Architecture for Text Engineering GATE is…. An architecture A macro-level organisational picture for LE software systems. A framework For programmers, GATE is an object-oriented class library that implements the architecture. A development environment For language engineers, computational linguists et al, GATE is a graphical development environment bundled with a set of tools for doing e.g. Information Extraction. Free software (LGPL). Mature robust software (in development since 1995). Download at Comes with… Some free components......and wrappers for other people's components Tools for: evaluation; visualise/edit; persistence; IR; IE; dialogue; ontologies; etc.

3(27) Applications; languages GATE has been used for a variety of applications, including: MUMIS: automatic creation of semantic indexes for multimedia programme material MUSE: a multi-genre IE system EMILLE: a 70 million word corpus of Indic languages Metadata for Medline (at Merck) Creation of metadata for Semantic Web Services; documentation using NLG HSE: summarisation of health and safety information from company reports OldBaileyIE: NE recognition on 17th century Old Bailey Court reports. AKT: language technology in knowledge management AMITIES: call centre automation Digital libraries / e-philology for ancient languages researchers Various Medical Informatics and database technology projects IE in Romanian, Bulgarian, Greek, Bengali, Spanish, Swedish, German, Italian, and French (Arabic, Chinese and Russian next year)

4(27) Some users… At time of writing a representative fraction of GATE users includes: Longman Pearson publishing, UK; BT Exact Technologies, UK; Merck KgAa, Germany; Canon Europe, UK; Knight Ridder (the second biggest US news publisher); BBN Technologies, US; Sirma AI Ltd., Bulgaria; Resco AB, Sweden/Finland/Germany; Glaxo Smith Kline Plc: drug-based navigation of Medline abstracts Master Foods NV: extraction of commodities events from news the American National Corpus project, US; Imperial College, London, the University of Manchester, Queen Mary College, UMIST, the University of Karlsruhe, Vassar College, ISI / the University of Southern California and a large number of other UK, US and EU Universities; the Perseus Digital Library project, Tufts University, US.

5(27) Architectural principles Non-prescriptive, theory neutral (strength and weakness) Re-use, interoperation, not reimplementation (e.g. diverse XML support, integration of tools like Protégé, Jena and Weka) (Almost) everything is a component, and component sets are user-extendable Component-based development An OO way of chunking software: Java Beans GATE components: CREOLE = modified Java Beans (Collection of REusable Objects for Language Engineering) The minimal component = 10 lines of Java, 10 lines of XML, 1 URL.

6(27) GATE Language Resources GATE LRs are documents, ontologies, corpora, lexicons, …… Documents / corpora: GATE documents loaded from local files or the web... Diverse document formats: text, html, XML, , RTF, SGML. Processing Resourcres Algorithmic components knows as PRs – beans with execute methods. All PRs can handle Unicode data by default. Clear distinction between code and data (simple repurposing) freebies with GATE e.g. Named entity recognition; WordNet; Protégé; Ontology; OntoGazetteer; DAML+OIL export; Information Retrieval based on Lucene

7(27) Visual Resources

8(27) Displaying Coreference Information

9(27) Displaying Syntactic Information

10(27) Lexicon Support – WordNet example

11(27) Relational Database … GATE Format Handlers HTML docs RTF docs XML docs Named entity Core- ference … ANNIE POS tagger Named entity Event extraction … Custom application 1 … Document content Document metadata Document format data Linguistic data File storage … Oracle/ PostgresQL A Language Analysis Example

12(27) Building IE Components in GATE (1) The ANNIE system – a reusable and easily extendable set of components

13(27) Building IE Components in GATE (2) JAPE: a Java Annotation Patterns Engine Light, robust regular-expression-based processing Cascaded finite state transduction Low-overhead development of new components Rule: Company1 Priority: 25 ( ( {Token.orthography == upperInitial} )+ {Lookup.kind == companyDesignator} ):companyMatch --> :companyMatch.NamedEntity = { kind = company, rule = “Company1” }

14(27) Performance Evaluation At document level – annotation diff At corpus level – corpus benchmark tool – tracking system’s performance over time

15(27) Regression Testing – Corpus Benchmark Tool

16(27) GATE is being used for development of (semi-)automatic methods for: linking web pages to Ontologies using Information Extraction; learning and evolving Ontologies via IE and lexical semantic network traversal. The Semantic Web and GATE

17(27) Populating Ontologies with IE

18(27) Protégé and Ontology Management

19(27) Information Retrieval Support Based on the Lucene IR engine

20(27) GATE Unicode Kit (GUK) Java provides no special support for text input (this may change) Support for defining additional Input Methods (IMs) currently 30 IMs for 17 languages Pluggable in other applications Editing Multilingual Data

21(27) Processing Multilingual Data All the visualisation and editing tools for ML LRs use enhanced Java facilities:

22(27) Dialogue Systems GATE is being used in the Amities project for automating call centres Creation of dialogue processing server components to run in the Galaxy Communicator architecture Easy adaptation of the portable IE components to work on noisy ASR output Robustness and speed of GATE components vital for real- time dialogue systems

23(27) The MUMIS project Multimedia Indexing and Searching Environment Composite index of a multimedia programme from multiple sources in different languages ASR, video processing, information extraction (Dutch, English, German), merging, user interface University of Twente/CTIT, University of Sheffield, University of Nijmegen, DFKI, MPI, ESTEAM AB, VDA Yorick Wilks, Hamish Cunningham, Horacio Saggion, Kalina Bontcheva, Diana Maynard, Oana Hamza, Cristian Ursu

24(27) The Whole Picture EN DE Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Sources IE NL Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Formal Text Trans criptions ASRASR Forma l Text Forma l Text Forma l Text Forma l Text Forma l Text Forma l Text Forma l Text Forma l Text Forma l Text Forma l Text Forma l Text Speech Signals Merging Final Annotations Forma l Text Forma l Text Forma l Text Anno- tations Multimedia Data Base Video & Audio Signal User Interface Query Results Ontology & Lexicon

25(27) User Interface

26(27) Play

27(27) Conclusion GATE: an infrastructure that lowers the overhead of creating & embedding robust NLP components Further information: Online demos, tutorials and documentation Software downloads Talks and papers