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TTC: Terminology Extraction, Translation Tools and Comparable Corpora
Helena Blancafort (1,2), Béatrice Daille (3), Tatiana Gornostay(4), Ulrich Heid(5), Claude Mechoulam(6)
(1)Syllabs, (2)Universitat Pompeu Fabra, (3)LINA, Université de Nantes, (4)Tilde, (5)IMS, Universität
Stuttgart, (6)Sogitec, (7)CTS, University of Leeds
The need for linguistic resources in any natural language application is undeniable. Lexicons and
terminologies play indeed a central role in any machine translation tool, regardless of the theoretical
foundations upon which the machine translation tool is based (e.g. statistical machine translation or
rule-based machine translation). The EU project TTC (“Terminology Extraction, Translation Tools
and Comparable Corpora”) aims at leveraging machine translation tools, computer-assisted
translation tools, and terminology management tools by automatically generating bilingual
terminologies from comparable corpora in several European Union languages (English, French,
German, Latvian and Spanish), as well as in Chinese and Russian. The TTC project will integrate
developed and existing tools in an online platform including a tool to compile and handle
comparable corpora, as well as a terminology management tool. The platform will be based on Web
Services and will use reputable open solutions such as UIMA (Unstructured Information
Management Architecture) and EuroTermBank.
The need for linguistic resources in any natural language application is undeniable. The problem is
especially difficult for translation applications because of cross-linguistic divergences and
mismatches that arise from the perspective of the lexicon. Lexicons and terminologies play indeed a
central role in any machine translation tool, regardless of the theoretical foundations upon which the
machine translation (MT) tool is based (e.g. statistical machine translation or rule-based machine
translation, example-based translation, etc).
project focuses on the automatic or semi-automatic acquisition of aligned bilingual
terminologies for computer-assisted translation and machine translation. To do this, important steps
of the project are the automatic extraction of monolingual terminologies and the bilingual alignment
of the extracted terminologies from multilingual corpora in specialized domains. Terminologies will
include single word terms (SWT) and multi-word terms (MWT), as well as their variations.
Terminologies may be extracted from parallel corpora, i.e. from previously translated texts, but
such corpora are scarce. Previously translated data is still sparse and only available for some pairs
of languages and few specific domains, such as Europarl (Koehn, 2005). Thus, no parallel corpora
are available for most of specialized domains, especially for emerging domains (such as renewable
energy). As a consequence, the project develops methods and tools for automatic extraction of
terminologies from comparable corpora, i.e. from “sets of texts in different languages that are not
translations of each other” (Bowker and Pearson, 2002, p.93). Moreover, TTC aims at developing
tools for gathering and managing comparable corpora and terminologies: a focused web crawler, a
tool to handle comparable corpora using the existing open source UIMA (Unstructured Information
) framework, and a terminology management tool. At the end of the
TTC project, a platform will be set up to combine those tools and to compile and manage
comparable corpora using standards (TMF, TBX) and UIMA framework. The open terminology
platform will support tasks such as terminology storage, search, editing and export, as well as the
reuse of Eurotermbank
. Translation of technical documents for the domains of aerospace and IT
documentation will be performed by end-users of the consortium using CAT and MT techniques to
assess impact of the TTC project outputs. This three-year project has been granted financial support
from the European Commission under the European Community’s Seventh Framework Programme
(FP7/2007-2013) and started in January 2010.
2 Main Goals
The main goals of the project are as follows:
a. Using comparable corpora
The TTC will be using comparable corpora and take advantage from the huge amount of
multilingual textual data available on the web (“Web as a Corpus” approach, Kilgarriff and
Grefenstette; 2003). As corpora compiled from the Web can be inconsistent and too variable, the
project develops a topical web crawler to gather comparable corpora from domain-specific Web
portals or using query-based crawling technologies with several types of conditional analysis. The
objective is to guarantee the monolingual comparability (i.e. the comparability between pairs of
texts in the same language), as well as the interlingual comparability of the compiled corpora by
identifying the most relevant criteria and measures, such as structural, modal or lexical criteria.
Besides, the elaborated typologies should be easily adaptable to other languages.
b. Using a minimum of linguistic knowledge for candidate term extraction
Term candidates and their relevant context partners (e.g. collocations) will be extracted from
corpora using available monolingual term extractors. However, the TTC platform plans to handle
also under-resourced European languages, i.e. languages with less available tools and resources.
Therefore, the scientific objective is the assessment of the minimal amount of language-specific
linguistic knowledge which is needed to identify term candidates and extract terminologies.
Moreover, as word translation is not always possible, we plan to extract MWT translations as well
as to pinpoint terminological gaps, i.e. terms that do not exist in the target language and therefore
need to be paraphrased. The extraction of MWTs and complex terms are crucial when dealing with
c. Defining and combining different strategies for term alignment
TTC’s objective concerning term alignment consists in improving methods for term alignment from
comparable corpora, especially for specialized domains and MWTs. For this purpose, we intend to
define, combine and evaluate lexical, contextual and corpora strategies. More specifically, we
explore compositional methods (use of synonyms and variants, computation of interlingual
representations), introduce depth in the context vectors used to express lexical contexts, and
improve the adequacy of specialized comparable corpora with other textual resources such as
parallel corpora or general language corpora (Morin et Daille, 2009; Daille, 2007) .
d. Developing an open platform for use with MT and CAT tools
The TTC consortium develops complementary tools in order to manage comparable corpora and
generated terminologies based on the UIMA framework and EuroTermBank. All developed and
existing tools will be integrated into a demonstration platform offering all necessary Web Services.
This platform will be easily integrated into various translation processing chains (including CAT
translation, rule-based MT and statistical MT). The French TTC partner LINA from the Université
de Nantes is building a French-speaking UIMA community in the domain of Natural Language
Processing. Some services have already been set up and are currently available on the UIMA
portal. UIMA wrappers for term extraction and alignment tools as well as UIMA collection
management tools will be developed during the project (Hernandez et al., 2010).
e. Demonstrating the operational benefits on MT tools and CAT tools
The main purpose of the TTC project is to propose solutions for translation in specialized domains
and for languages with scarce linguistic resources. Besides, one of the objectives is that the
proposed solutions can be rapidly used in an operational environment. As a consequence, the
benefits of the developed solutions will be assessed regarding the gain in productivity to generate
the terminologies, but also regarding the quality of translation, and the amount of invested linguistic
knowledge – so as to reduce the gaps in language coverage by requiring as little knowledge as
The impact on statistical MT will be evaluated as well. The work outlined in this project will
leverage statistical MT performance in two ways. First, it will reduce the number of OOV words
(out-of-vocabulary words, i.e. SWTs and MWTs which do not appear at all in the parallel data on
which the statistical MT system is trained). Secondly, it will automatically determine additional
translation candidates for SWT and MWT which occur either infrequently in the parallel corpora or
which occur with a sense that is only correct in the domain of the parallel corpus and not in the
domain of the translation to be performed.
3 Overall strategy of the work plan
The TTC project will develop a platform for automatically generating specialized monolingual and
multilingual terminologies using comparable corpora and relying on existing open technologies
(UIMA) and standards (TMF, TBX). The next figure illustrates the architecture of the expected
multilingual terminology mining chain. Generated terminologies will be plugged into existing MT
and CAT tools in order to improve their performance, especially for specialized domains and/or
Figure 1: Architecture of the multilingual terminology mining chain
The work breakdown structure in figure 2 shows the organization of the tasks that will be
accomplished during the project.
Figure 2: Work breakdown structure
Currently, requirements are being defined. This is being done in close collaboration with end users
and by consulting external stake-holders. A survey about terminology and corpora practices in the
translation and localization industry has been launched recently
. First results show today’s
demands from translation and localization professionals: consolidated accesses to terminology
resources and consolidated terminology platforms, consistency check and support features, corpora
and domain oriented solutions, as well as user-friendly interfaces (Gornostay, 2010). Moreover,
ongoing work includes the definition of functional specifications and exchange formats according to
international standardization initiatives such as ISO TC-37 and the EU project CLARIN
The survey can be accessed here: http://www.visidati.lv/aptauja/345124026/
4 Expected Results and Impacts
The expected results and impacts of TTC include:
Domain-specific resources for renewable energy and computer science in seven languages
(monolingual as well as bilingual aligned terminologies).
Comparable corpora, lemmatized and POS-tagged.
Generic methods and tools for automatic extraction of terminologies and alignment algorithms, as
well as for recognizing term variants, for term inflection and morphological analysis.
Focused crawler to compile comparable corpora.
Open source suit tools to handle comparable corpora and to extract terminologies.
Online terminology platform.
Enhancement of existing on-line tools for MT (MOSES).
The project consortium brings together seven partners from four different countries (France,
Germany, Latvia and UK). Project leader is French laboratory LINA (Laboratoire d’Informatique
de Nantes) from Université de Nantes. Further academic partners are the Centre for Translation
Studies (CTS) from University of Leeds, as well as Institut für maschinelle Sprachverarbeitung
(IMS) from Universität Stuttgart. IMS contributes to research on monolingual term extraction
(MWT and SWT), on morphology and syntax. CTS works on corpus collection and term extraction
activities, and leads the evaluation of the impact of TTC results on MT tools. Industrial partners are
the French companies Sogitec and Syllabs, as well as the Latvian company Tilde. Syllabs works on
the focused crawler, Tilde is responsible for the terminology platform. As an end user of translation
and terminology tools in the aerospace domain, Sogitec will perform the evaluation of TTC impacts
on computer-assisted translation tools. Finally, Eurinnov is responsible for administrative, financial
and legal management as well as scientific and technical coordination.
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Engineering, volume 2 of Benjamins Current Topics, pages 163-177. John Benjamins, 2007. ISSN
Gornostay, T. (2010). “Terminology Management In Real Use”. The 5th International Conference in
Commemoration of Rajmund Piotrowski (1922-2009) “Applied Linguistics in Science and
Education”, 25-26 March, 2010, Saint-Petersburg, Russia.
Kilgarriff, A and G. Grefenstette. (2003). “Web as Corpus: Introduction to the Special Issue”.
Computational Linguistics 29 (3): 333-347.
Koehn. P. (2005). “Europarl: A Parallel Corpus for Statistical Machine Translation”. MT Summit
Hernandez, N.; Poulard, F. ; Vernier, M. and Rocheteau, J. (2010). “Building a French-speaking
community around UIMA, gathering research, education and industrial partners, mainly in Natural
Language Processing and Speech Recognizing domains”. (to appear in "New Challenges for NLP
Frameworks", workshop at LREC 2010 : Malta).
Morin, E. and Daille, B. (2009). “Compositionality and lexical alignment of multi-word terms”.
Language Resources and Evaluation. Vol. 44 Number 1-2. Springer Netherlands.