Nine terminology extraction tools – Are they useful for translators?

Terminology extraction tools (TETs) have become an indispensable resource in education, research and business. Today, users can find a great variety of terminology extraction tools of all kinds, and they all offer different features. Apart from many other areas, these tools are especially helpful in the professional translation setting. We do not know, however, if the existing tools have all the necessary features for this kind of work. In search for the answer, we looked at nine selected tools available on the market to find out if they provide the translators’ most favorite features.


Terminology extraction tools and their areas of application

The purpose of TETs is to help users build terminological resources in a (semi-) automatic way. The need for such resources comes mostly from the growing needs in information management and translation, which make it increasingly necessary to have some automated assistance when performing terminology-related tasks. Companies, freelancers and professionals in various linguistic fields can employ these tools to build a glossary, thesaurus or terminological dictionary that they use directly in their work. Moreover, terminology extraction is embedded in a number of natural language processing and linguistic research tasks, such as automatic indexing; machine translation; information extraction; creation of ontologies and knowledge bases; and corpus analysis. Despite this broad range of applications, these tools are often designed for one specific purpose, which consequently makes their usage challenging when employed in a different setting.

One of the most important areas where terminology extraction is extremely helpful is in the translation industry. Today, more and more language service providers (LSPs) as well as freelance translators and interpreters understand the benefits of automatizing terminology tasks. It not only allows them to quickly identify the domain of the documents they are dealing with, but also to easily find words and phrases that need special attention. While translating terminological units, in many cases it is necessary to consider the domain and look up the term equivalents in special resources such as terminology databases. In addition, it helps maintain terminological consistency throughout the project between all the parties involved: the translator, the LSP and the client.

Apart from saving time, another significant advantage of using TETs instead of a manual terminology search is the opportunity to specify different search criteria, which allows for customization of the search query to a particular task. This allows users to see all kinds of information they need about the term, and also to narrow the search and filter the results depending on what they are looking for. As an example, many state-of-the-art TETs will show linguistic and statistic information about the term or the context where it appears and they might specify the number of words in the term as well as provide other useful features. Unfortunately, not every TET offers a full set of desirable features and settings, which sometimes makes it challenging to find the perfect tool for the task at hand. Apart from the functionalities they offer, TETs also differ as to the environment they work in. For instance, standalone installable tools require an installation process and work as independent computer programs. Web-based tools also exist and work within a browser. And finally, there is reusable software that facilitates the development of larger applications, called frameworks.

Considering the existing variety, it is not clear how a professional translator is to proceed when choosing a TET suitable for the job. As we will see, there are some TETs that are specifically created for translators. But do they have all the necessary characteristics for translators? And, furthermore, what exactly are these characteristics?


Standalone terminology extraction tools

Standalone software is probably the most popular type of software today, and TETs are no exception. Standalone TETs can be installed on a computer and operate independently of any other device or system.


SDL MultiTerm Extract is one of such applications. It is a component of SDL MultiTerm, a commercial terminology management tool that provides one solution to store, extract and manage multilingual terminology. MultiTerm exists as a standalone application and can also be integrated in SDL Trados Studio. It is one of the few tools designed specifically to be used by translators and is probably the most well-known TET in the translation industry. This terminology extraction system locates potential monolingual and bilingual terminology in documents and translation memories using a statistic-based method. The user can validate the extracted candidate terms by looking at a monolingual or bilingual concordance. A big advantage of this tool is its support for any language, including Unicode languages. In addition, it offers a number of functionalities that are useful in different translation scenarios: the ability to compile a dictionary from parallel texts; flexible filtering to ensure that only the most frequent candidate terms are extracted; storage for an unlimited number of terms in any language; and the capability to import and export glossaries from and to different technology environments. In addition, its integration with SDL Trados Studio gives access to many convenient term management functions, such as manually adding a variety of metadata information to the terms (such as synonyms, context, definitions, illustrations, part-of-speech tags and URLs), and searching not only the indexed terms but also their descriptive fields.


SimpleExtractor, as its name implies, offers significantly fewer functionalities compared to the previous tool. It is a commercial TET developed by DAIL Software S.L. for Mac OS, Linux and Windows platforms. This clean and easy-to-use standalone Java application was designed to automatically extract the most frequent words and multiword terms from English, Portuguese, Spanish, French and Russian documents. SimpleExtractor not only permits to extract a list of terms (from one to seven words), but also specify the minimum and maximum number of occurrences of a term. SimpleExtractor also offers an option to load stopword lists, an advanced functionality for searching through the extracted list of terms. This translates to the ability to explore all the contexts where a specific term appears; to edit the term text, to filter the extracted terms according to the number of words that form them; and to sort the displayed output by any of its fields (frequency, term and context in alphabetical order). Finally, SimpleExtractor permits printing or exporting to a file (PDF, DOC, CSV or TXT) of all the extracted terms, as well as their frequencies and corresponding contexts.



TermSuite is an open source and platform-independent TET written in Java and distributed under the Apache License 2.0. It was developed within the scope of the TTC (Terminology Extraction, Translation Tools and Comparable Corpora) project, whose purpose was to design a tool capable of extracting bilingual terminology from comparable corpora in six languages: English, French, German, Spanish, Chinese and Russian. TTC TermSuite’s architecture is composed of three modules: the Spotter, the Indexer and the Aligner. The Spotter module is responsible for preprocessing the input monolingual corpus, meaning it performs tokenization, part-of-speech tagging, stemming and lemmatization. Then, the Indexer module uses both a statistic and a linguistic-based approach to extract monolingual terminology from a monolingual corpus processed by the Spotter. Finally, the Aligner computes the translation of a source terminology into a target language. The source and target terms required are those already computed by the Indexer module, which means that the previous two steps should be repeated for the target language. The user can choose from several alignment options, such as the selection of the maximum number of translation candidates for a given source term, the use of similarity measures to compare the contexts of the term in the source and the target languages, amongst other advanced settings. Once all the parameters are set, it is possible to view and explore all the translation candidates ranked according to their similarity score within the tool or use the output XML file for other purposes.


Web-based terminology extraction tools

Although standalone TETs still are predominant in today’s market, future web-based technologies will certainly evolve by migrating all standalone features to a web-based environment, which will allow these tools to take over market leadership in the near future. As we will see, there are already some examples of this trend. The advantages are that web-based TETs, compared to standalone tools, do not require any prior installation as they can be accessed within a web browser, and that they make use of web technologies. Although most web-based TETs are often integrated as features in cutting-edge web-based applications with a wider purpose, such as managing corpora or terminology (such as Sketch Engine and Terminus, respectively), there also exist tools like the TET by Translated, which were developed with the proper purpose of terminology extraction.



Sketch Engine is an online tool created by Lexical Computing Ltd for building and managing corpora, which along with a number of corpus-processing features includes terminology extraction. It can be accessed under a paid commercial or academic license and supports 82 languages. This tool offers both monolingual and multilingual extraction. When extracting monolingual terminology, the user can choose whether to extract only single words (keywords) or multi-word terminological units (terms). In the output, the user can see the keywords or terms, links to the five most relevant Wikipedia articles for each of them, the term’s score, its frequency in the searched corpus, and its frequency in the reference corpus. There are a variety of search options that can be tuned. For instance, the user can choose a different reference corpus, decide whether to search for words or lemmas, and accentuate low- or high-frequency keywords according to the preferences. The output can be downloaded as a TBX or CSV file. In order to perform multilingual term extraction the user needs to upload a TMX file with a parallel corpus aligned on the sentence or paragraph level. The terminology is first extracted within each language resulting in lists of candidate terms. In the second step, the system searches for such pairs of candidates that colocate in the parallel documents most often. The resulting list of candidate pairs (terms in two languages) is then presented to the user. Results can be saved in a TBX or TXT file, which is especially convenient for computer-assisted translation (CAT) tool users.



Translated s.r.l. is an LSP-developed, web-based tool that can be accessed directly on the company’s website. It was created in order to help translators with their translation jobs by identifying the difficulties in the text and simplifying the process of creating glossaries. Up to the current date it supports only English, Italian and French. The system output includes the top 20 terms ranked by their score. In addition, the terms are given as hyperlinks to the corresponding Google search results. Below the list of terms the tool also shows all the terms in their full-sentence context. In order to easily differentiate the terms, each term is highlighted by a different color. In general, this tool is quite simple compared to the others, but can provide a fast and free solution any time it is needed.



Terminus is a web-based application for corpus and terminology management developed at the University Pompeu Fabra, Spain, and it can be accessed by software licensing. The purpose of this tool is to integrate the complete process of terminographic work: textual corpus search, compilation and analysis, term extraction, glossary and project management, database creation and maintenance, and dictionary edition. This is done with the help of a number of articulated modules, including the Analysis module, which has a semiautomatic term extraction feature. The extraction process has two options: the user can train a term extractor in a specific domain by incorporating an electronic dictionary containing terms of the same field, or simply apply a generic ready-to-use term extractor to any textual corpus. In addition, one can use other features to extract term candidates, such as the n-gram extractor, bi-gram extraction with association measures, keywords, and later manually validate relevant terms.



Frameworks are different from the other two types of tools because they are not complete software products but reusable software environments or libraries that can be used or even completely integrated in larger translation software applications, products or solutions. In particular, systems of this type are often used in information retrieval, where identification and indexing of terminology serves as an aid to information retrieval queries. In detail, the purpose of terminology extraction for both information retrieval and document retrieval is to isolate terms that contain enough informational content to support retrieval based on the queries supplied when querying a set of documents.



Keyphrase Extraction Algorithm (Kea) is a framework specially designed for automatically assigning terms to a document (also known as keyphrase indexing). Kea is a platform-independent toolkit implemented in Java and distributed under the GNU General Public License. In detail, this framework can either be used for free indexing or for indexing with a controlled vocabulary. When used as free indexing, Kea looks for significant terms in a document. The free indexing option can be applied to any document and working language (as long as the corresponding stopword file and stemmer are provided). The controlled indexing, on the other hand, has the advantage that all documents are indexed in a consistent way disregarding their wording as the algorithm only collects those n-grams that match thesaurus terms.



Rainbow is a simple, yet powerful open source platform-independent terminology extraction tool written in Java that uses statistic-based methods to automatically extract terms from multiple files and formats in any language. It is based on the Okapi Framework, a free, open source and cross-platform framework that has a set of components and applications designed to help engineers, developers, translators and project managers involved in localization and translation-related tasks.



Java Automatic Term Extraction (JATE) is a JAVA toolkit that comprises several state-of-the-art term extraction algorithms. The motivation for this tool is three-fold: make available several automatic term extraction algorithms for the research community; encourage developers to build their methods under a uniform framework; and enable comparative studies between different term extraction algorithms. JATE’s workflow follows the typical TET steps: extract candidate terms from a corpus using linguistic tools; extract the candidates’ statistical features from the corpus; and apply automatic terminology extraction algorithms to score the candidate terms domain representativeness based on their statistical features. So far, JATE’s current version includes twelve state-of-the-art statistical algorithms.


Translators’ preferences and opinions

As we mentioned above, translation is one of the most important applications of terminology extraction. However, extraction tools have not yet become a common part of the professional translation workflow. This was demonstrated by Anna Zaretskaya, Gloria Corpas Pastor and Míriam Seghiri Domínguez’s 2015 user survey, which was replied to by over 600 translation professionals, and which showed that only 25% of the respondents regularly resorted to terminology extraction in their work. It could be due to unsatisfying performance of the existing tools, their interface design, or simply to translators’ lack of awareness of these tools and of the benefits they can yield.

We have already seen that these tools can differ as to various characteristics, such as their interface type (standalone, web-based or reusable libraries), the document formats they support, the languages they work with, as well as their different search options. According to the survey findings, 27% of the respondents preferred to have a terminology extraction feature within their CAT tool instead of in separate software. Some translators, however, preferred a web-based application (9%) or installing a standalone tool on their computer (8%). Nevertheless, the majority (56%) reported that they did not have any preference regarding the tool’s interface. The fact that translators prefer to have a system integrated in their CAT tool is related to the general tendency of CAT tools to include more and more different features. Indeed, translators have to deal with a great number of tools that help them automatize different stages of the translation process, so they prefer having one tool with multiple functions rather than having to look for and in many cases pay for several tools.

The most useful extraction feature according to the survey’s participants was bilingual term extraction. In fact, considering that within a translation workflow, terminology extraction is performed with the final objective to translate the extracted terms, it is more convenient to have the terms extracted in the two languages simultaneously. Bilingual extraction is much harder to perform than only monolingual as it requires a good word alignment system, so not many existing tools offer this feature. In particular, among the tools we considered in the previous section only SDL MultiTerm Extract and Sketch Engine have bilingual extraction. Similarly, TermSuite also offers translation candidates for the extracted monolingual terms, which is a different procedure, but still leads to the same results: terms in two languages.

The second ranked feature was the possibility to compare the context of the term in the source and the target language, which is another type of bilingual analysis suitable for the translation task. This feature is also quite rare, and of all the considered tools, only SDL MultiTerm Extract allows such analysis. The possibility to validate terms or, in other words, choose the terms that should be extracted instead of extracting all terms was ranked third and is also considered useful for translators. This feature is offered by almost all systems, except for TermSuite and Translated. Compiling a bilingual dictionary from parallel texts is another useful feature, which is offered only by SDL MultiTerm Extract and by TermSuite. Additionally, the respondents considered it useful to extract context together with terms or to see examples from the corpus. This is a common feature for many of the studied tools, including SDL MultiTerm Extract, SimpleExtractor and Translated.

Other features that were considered include: support for different file formats; sort terms by frequency; support for many languages; specify the minimal number of occurrences of the words; show linguistic information about the term; and select the maximum number of translations for one term. All of them were considered useful, but were not among the most useful features.

And finally, there were some features the respondents considered to be not as important. One of them was the stopword list option: some of the tools, like SimpleExtractor, allow users to choose whether to use a stopword list, and others use it by default. Choosing the minimum and the maximum number of words per term, which was also among the least useful features, can be tuned by all the mentioned terminology extraction frameworks, for example. And finally, term statistics, which to some extent are provided by all tools, were not very important for most translators.



Although terminology extraction plays an important role in several disciplines such as linguistic research or language teaching, it is in the field of translation where its advantages are fully exploited and integrated in the workflow. An example of that is the use of bilingual term extraction, compiling dictionaries and comparing context in different languages as essential features for translators’ work. In addition, it is also very useful for translators to see the terms in their context in order to understand their meaning and be able to find an adequate translation equivalent. Not all existing tools, however, provide these functionalities. We suggest that developing tools more suitable for the purpose of translation could help professionals in the industry take better advantage of terminology extraction technology. This has to be done, first of all, by taking into account the user requirements. As a step further in this direction, it would be necessary to investigate in more detail translators’ attitudes toward these tools and especially the reasons that prevent the vast majority of professional translators from adopting them. For instance, many translators might not be aware of their existence or understand their purpose, do not have time to learn how to use another complicated interface, or simply have other established procedures for dealing with terminology.