{"id":1278,"date":"2025-07-28T13:43:25","date_gmt":"2025-07-28T13:43:25","guid":{"rendered":"https:\/\/www.ata-divisions.org\/LTD\/?p=1278"},"modified":"2025-12-31T21:08:15","modified_gmt":"2025-12-31T21:08:15","slug":"ata-tektalks-is-oneclick-terms-the-right-tool-for-you-an-ata-language-technology-division-webinar","status":"publish","type":"post","link":"https:\/\/www.ata-divisions.org\/LTD\/ata-tektalks-is-oneclick-terms-the-right-tool-for-you-an-ata-language-technology-division-webinar\/","title":{"rendered":"ATA TEKTalks: Is OneClick Terms the Right Tool for You? An ATA Language Technology Division Webinar"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"1278\" class=\"elementor elementor-1278\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c584203 e-flex e-con-boxed e-con e-parent\" data-id=\"c584203\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-53c8281 elementor-widget elementor-widget-image\" data-id=\"53c8281\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"182\" height=\"96\" src=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/OneClick-logo.png\" class=\"attachment-large size-large wp-image-1279\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2052972 elementor-widget elementor-widget-text-editor\" data-id=\"2052972\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><i style=\"font-size: 1.8rem;\">By Anne Chemali<\/i><\/p><p style=\"line-height: 115%;\"><i>July 28, 2025<\/i><\/p><p class=\"MsoNormal\" style=\"line-height: 115%;\">The ATA Language Technology Division (LTD) held its quarterly ATA TEKTalk on July 10, 2025, featuring Ond\u0159ej Matu\u0161ka, a linguist and the head of sales at SketchEngine, a corpus system developed by Lexical Computing, a company based in Brno, in Czech Republic. His role includes promoting the use of corpora among linguists and language professionals and running training events and workshops. Ond\u0159ej also contributes to developing the user interface and improving the user experience of SketchEngine.<\/p><p class=\"MsoNormal\" style=\"line-height: 115%;\">SketchEngine is a comprehensive language analysis system used by various language professionals including linguists, teachers, translators, interpreters, and lexicographers. While the system contains many tools primarily designed for academic language research, one particular feature &#8211; terminology extraction &#8211; is especially valuable for translators and interpreters.<\/p><p style=\"line-height: 115%;\">\u00a0<\/p><p class=\"MsoNormal\" style=\"line-height: 115%;\">The developers created a separate, simplified web interface called OneClick Terms. It is designed to be streamlined and user-friendly, with a simple &#8220;START HERE&#8221; button.<\/p><p><b>What it term extraction and how is it done?<\/b><\/p><p>Term extraction refers to identifying words or phrases that have a specific meaning in a given context, or in a specific document. Linguists use term extraction to build a list of phrases which need to be translated with special care or need to be considered with special attention, because they carry an important meaning in the document. It is the preliminary work before building a glossary for your translation or for your interpreting assignment, which you can then use in association with a CAT tool or any other equivalent tool.<\/p><p>The best terminology extraction tool will always be the human brain, Ond\u0159ej said. The quality of human extraction is in fact very high, but unfortunately, the speed is also very slow. If you&#8217;ve got a document of two pages, the best way to extract terminology is just to read it and underline the terms. But if you&#8217;ve got 100,000 pages, it\u2019s impossible to do so. So, how do we imitate the human brain?<\/p><p>What the human brain does to identify terminology is to somehow take what it reads and compare it to its linguistic experience, to what it knows, or to what it has in its memory about the language. OneClick Terms was designed to emulate the human brain\u2019s tasks.<\/p><p><b>OneClick Terms interface Demo<\/b><\/p><p><b>\u00a0<\/b><span style=\"font-size: 1.8rem;\">The interface is designed to be user friendly and is so intuitive that the learning curve is extremely flat. Note that 36 languages are currently supported. Languages appearing in the language list with a yellow star offer \u00a0a higher level of support. To start a term extraction, the user selects two languages and then clicks on the \u201cSTART HERE\u201d button.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8e0ed3d elementor-widget elementor-widget-image\" data-id=\"8e0ed3d\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"624\" height=\"403\" src=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Monolongual-Bilingual.png\" class=\"attachment-large size-large wp-image-1280\" alt=\"\" srcset=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Monolongual-Bilingual.png 624w, https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Monolongual-Bilingual-300x194.png 300w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-412ba85 elementor-widget elementor-widget-text-editor\" data-id=\"412ba85\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-size: 1.8rem;\">The terminology extraction tool offers three ways to extract terms: from monolingual texts, from bilingual aligned texts (like translation memories in TMX or XLIFF format), or from unaligned bilingual texts that are translations of each other, which the system will automatically align.<\/span><\/p><p>\u00a0<b style=\"font-size: 1.8rem;\">Monolingual extraction process:<\/b><span style=\"font-size: 1.8rem;\"> The demonstration used an English PDF from the Official Journal of the European Union. The tool extracts text, assigns parts of speech, analyzes morphology (gender, case, etc.), and categorizes results into single words (useful for acronyms and product names) and multi-word phrases. Terms are presented in their basic forms (singular, first case) regardless of how they appear in the document.<\/span><\/p><p>\u00a0<b style=\"font-size: 1.8rem;\">Bilingual extraction process:<\/b><span style=\"font-size: 1.8rem;\"> Using English and Spanish versions of the same EU document, the tool converts text to plain text, assigns grammatical properties, considers language-specific rules (like gender agreement between adjectives and nouns), aligns terms between documents, and presents multiple translation candidates with the ability to view source sentences for verification.<\/span><\/p><p>\u00a0<b style=\"font-size: 1.8rem;\">The performance advantage:<\/b><\/p><p>The goal of OneClick Terms is to find the right balance between extracting terms that are not really terms and missing an important term in the document.<\/p><p>\u00a0<span style=\"font-size: 1.8rem;\">Here&#8217;s a summary of the top features mentioned for increasing linguist productivity:<\/span><\/p><p>\u00a0<span style=\"text-indent: -0.25in; font-size: 1.8rem;\">1.<\/span><span style=\"text-indent: -0.25in; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; font-size-adjust: none; font-kerning: auto; font-optical-sizing: auto; font-feature-settings: normal; font-variation-settings: normal; font-variant-position: normal; font-variant-emoji: normal; font-stretch: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';\">\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">OneClick Terms considers the grammar and linguistics rules of each language, not just statistics.<\/span><\/p><p><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">\u00a02.<\/span><span style=\"text-indent: -0.25in; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; font-size-adjust: none; font-kerning: auto; font-optical-sizing: auto; font-feature-settings: normal; font-variation-settings: normal; font-variant-position: normal; font-variant-emoji: normal; font-stretch: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';\">\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">Cleaner output with less noise: OneClick Terms produces much cleaner results compared to other terminology extraction tools, meaning there are fewer irrelevant or incorrect terms in the output.<\/span><\/p><p><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">3.<\/span><span style=\"text-indent: -0.25in; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; font-size-adjust: none; font-kerning: auto; font-optical-sizing: auto; font-feature-settings: normal; font-variation-settings: normal; font-variant-position: normal; font-variant-emoji: normal; font-stretch: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';\">\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">Faster review process: Because the output contains less noise and irrelevant information, linguists can work through the extracted terms more quickly and efficiently.<\/span><\/p><p><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">4.<\/span><span style=\"text-indent: -0.25in; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; font-size-adjust: none; font-kerning: auto; font-optical-sizing: auto; font-feature-settings: normal; font-variation-settings: normal; font-variant-position: normal; font-variant-emoji: normal; font-stretch: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';\">\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">Standardized term presentation: Terms are automatically presented in their basic grammatical forms (singular, base case) rather than in the various declined, plural, or case-specific forms they might appear in within the source text. It handles morphological variations across different languages.<\/span><\/p><p><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">5.<\/span><span style=\"text-indent: -0.25in; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; font-size-adjust: none; font-kerning: auto; font-optical-sizing: auto; font-feature-settings: normal; font-variation-settings: normal; font-variant-position: normal; font-variant-emoji: normal; font-stretch: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';\">\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span><span style=\"text-indent: -0.25in; font-size: 1.8rem;\">The ultimate word selection belongs to the users: They can accept one of the recommended terms, enter a new term of choice, or they can eliminate some terms from the termbase export altogether.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-222e814 elementor-widget elementor-widget-image\" data-id=\"222e814\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"624\" height=\"279\" src=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Parallel-concordance.png\" class=\"attachment-large size-large wp-image-1281\" alt=\"\" srcset=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Parallel-concordance.png 624w, https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Parallel-concordance-300x134.png 300w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c75bf7b elementor-widget elementor-widget-text-editor\" data-id=\"c75bf7b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b style=\"font-size: 1.8rem;\">User settings<\/b><\/p><p>OneClick Terms offers several customization settings to refine terminology extraction results:<\/p><p><b style=\"font-size: 1.8rem;\">Deny list feature:<\/b><span style=\"font-size: 1.8rem;\"> Users can exclude specific words from results by copying\/pasting terms or uploading a file containing words to be filtered out.<\/span><\/p><p><b>Character requirements, including:<\/b><\/p><ul style=\"margin-top: 0in;\" type=\"disc\"><li>Default setting requires terms to contain at least one letter (excludes pure numbers)<\/li><li>Option to allow &#8220;only letters and numbers&#8221; (removes hyphens, dashes, slashes)<\/li><li>Option to include only lowercase terms to avoid proper nouns (not recommended for all languages)\u00a0<\/li><\/ul><p><b>Specificity slider:<\/b> A slider allows users to adjust the balance between rare and common words:<\/p><ul style=\"margin-top: 0in;\" type=\"disc\"><li>Sliding toward &#8220;Rare words&#8221; prioritizes highly specific terminology<\/li><li>Sliding toward &#8220;Common words&#8221; includes less specific terms that might still be considered terminology<\/li><li>Example given: &#8220;average value&#8221; &#8211; could be terminology but is also used in general language<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-34d1872 elementor-widget elementor-widget-image\" data-id=\"34d1872\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"624\" height=\"453\" src=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Settings-1.png\" class=\"attachment-large size-large wp-image-1282\" alt=\"\" srcset=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Settings-1.png 624w, https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Settings-1-300x218.png 300w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-009e4fe elementor-widget elementor-widget-image\" data-id=\"009e4fe\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"624\" height=\"427\" src=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Settings-2.png\" class=\"attachment-large size-large wp-image-1283\" alt=\"\" srcset=\"https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Settings-2.png 624w, https:\/\/www.ata-divisions.org\/LTD\/wp-content\/uploads\/2025\/07\/Settings-2-300x205.png 300w\" sizes=\"(max-width: 624px) 100vw, 624px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ed040b2 elementor-widget elementor-widget-text-editor\" data-id=\"ed040b2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b style=\"font-size: 1.8rem;\">How does terminology extraction work in conjunction with<br \/>CAT tools?<\/b><\/p><p>The tool essentially streamlines the process of detecting and cataloging client-specific terminology for use in translation projects.<br \/>When translators receive assignments from new customers, they may not be<br \/>familiar with the client&#8217;s specific terminology, even if they know the general<br \/>field. Companies often have their own unique terminology conventions.<\/p><p>\u00a0<span style=\"font-size: 1.8rem;\">OneClick Terms serves as an efficient method for building\u00a0<\/span><span style=\"font-size: 1.8rem;\">these terminology databases. Once the user is done reviewing the extracted term\u00a0<\/span><span style=\"font-size: 1.8rem;\">candidates, the entire list can be exported in multiple formats (Excel, text,\u00a0<\/span><span style=\"font-size: 1.8rem;\">TBX), then imported in a CAT tool. CAT tools can check terminology usage, but\u00a0<\/span><span style=\"font-size: 1.8rem;\">they require a reliable pre-populated termbase to function effectively.<\/span><\/p><p>\u00a0<b style=\"font-size: 1.8rem;\">Background mechanics behind OneClick Terms<\/b><\/p><p><b>\u00a0<\/b><span style=\"font-size: 1.8rem;\">Traditional term extraction tools use n-gram frequency\u00a0<\/span><span style=\"font-size: 1.8rem;\">analysis, where n-grams are sequences of words (e.g., &#8220;I love you&#8221; is\u00a0<\/span><span style=\"font-size: 1.8rem;\">a 3-gram, &#8220;I love&#8221; is a bi-gram). These tools identify word sequences\u00a0<\/span><span style=\"font-size: 1.8rem;\">that appear frequently in documents, assuming high frequency indicates\u00a0<\/span><span style=\"font-size: 1.8rem;\">terminology. They may include stop lists to exclude common words like\u00a0<\/span><span style=\"font-size: 1.8rem;\">conjunctions or articles.<\/span><\/p><p>\u00a0<span style=\"font-size: 1.8rem;\">But the standard definition of a term as &#8220;a word or\u00a0<\/span><span style=\"font-size: 1.8rem;\">phrase with specific meaning within a particular domain&#8221; is difficult to\u00a0<\/span><span style=\"font-size: 1.8rem;\">program into computer systems because determining &#8220;specific meaning&#8221;\u00a0<\/span><span style=\"font-size: 1.8rem;\">is complex for automated processes.<\/span><\/p><p>\u00a0<span style=\"font-size: 1.8rem;\">Terminology extraction is actually highly subjective, not\u00a0<\/span><span style=\"font-size: 1.8rem;\">objective. Here are examples:<\/span><\/p><ul style=\"margin-top: 0in;\" type=\"disc\"><li>&#8220;Return on investment<br \/>analysis model&#8221; &#8211; should this be one term or split into &#8220;return<br \/>on investment&#8221; and &#8220;analysis model&#8221;?<\/li><li>How about &#8220;Median<br \/>value sample size&#8221;? &#8211; what qualifies as a true term versus general<br \/>language?<\/li><\/ul><p style=\"margin-left: .25in;\">\u00a0<span style=\"font-size: 1.8rem;\">Practically, rather than asking &#8220;Is it a term?&#8221;\u00a0<\/span><span style=\"font-size: 1.8rem;\">the better question is &#8220;Is it useful to include it in my terminology\u00a0<\/span><span style=\"font-size: 1.8rem;\">database?&#8221; This focuses on practical utility for consistent translation\u00a0<\/span><span style=\"font-size: 1.8rem;\">rather than academic classification. Even non-technical phrases might be worth\u00a0<\/span><span style=\"font-size: 1.8rem;\">including if they need consistent translation across a project.<\/span><\/p><p>\u00a0<b style=\"font-size: 1.8rem;\">The frequency marker:<\/b><\/p><p>Instead of traditional definitions, a term is redefined as\u00a0something that appears more frequently in the domain-specific document than in\u00a0general language &#8211; a concept that can be programmed into computers.<\/p><p>OneClick<b> Terms <\/b>compares the words it finds in the\u00a0uploaded documents to a massive general language corpus (60 billion words in\u00a0English) that covers all topics and represents language in general use.<\/p><p>\u00a0<b style=\"font-size: 1.8rem;\">The steps of the comparison process are the following:<\/b><\/p><ol style=\"margin-top: 0in;\" start=\"1\" type=\"1\"><li>Documents are converted to\u00a0text<\/li><li>Words are lemmatized\u00a0(assigned basic forms so plurals\/singulars are treated as the same)<\/li><li>Parts of speech are tagged<\/li><li>&#8220;Term grammar&#8221;\u00a0rules specific to each language are applied, as each language has rules\u00a0defining what constitutes a term structure, for example:<\/li><\/ol><ul style=\"margin-top: 0in;\" type=\"disc\"><li>English: noun, two nouns,\u00a0adjective + noun, etc.<\/li><li>Spanish: different rules\u00a0(can&#8217;t have two nouns together without preposition\/article)<\/li><\/ul><p style=\"margin-left: 0.5in; text-align: left;\">\u00a0<b style=\"font-size: 1.8rem;\">Frequency comparison process:<\/b><span style=\"font-size: 1.8rem;\"> The tool identifies\u00a0<\/span><span style=\"font-size: 1.8rem;\">potential terms based on grammatical patterns, then compares their frequency in\u00a0<\/span><span style=\"font-size: 1.8rem;\">the document versus the general corpus:<\/span><\/p><ul style=\"margin-top: 0in;\" type=\"disc\"><li>Higher frequency in\u00a0document than general language = likely term<\/li><li>Much lower frequency in\u00a0general corpus = even stronger term candidate<\/li><li>Equal or higher frequency\u00a0in general language = not a term<\/li><\/ul><p>Will AI be able to perform term extraction?<\/p><p>While AI can find some terms, it doesn&#8217;t complete the\u00a0terminology extraction task comprehensively, making it unsuitable for this\u00a0specific application despite its usefulness in other areas.<\/p><p>Despite the company using AI for other purposes, AI is not\u00a0well-suited for terminology extraction. Because AI learns from human-produced\u00a0texts and data, it can only identify terms that were explicitly marked as terms\u00a0in its training data &#8211; essentially terms that already exist and have been\u00a0previously identified.<\/p><p>\u00a0<\/p><p>Terminology extraction tools should be able to identify\u00a0completely new terms that have never existed before, including company-specific\u00a0terminology that no other organization uses. The speaker gives an example of\u00a0working at a company that had unique terms not used elsewhere.<\/p><p>\u00a0<\/p><p>In a direct test using the same document presented earlier:<\/p><p style=\"margin-left: .5in;\">An AI tool found approximately 85\u00a0terms<\/p><p style=\"margin-left: .5in;\"><span style=\"font-size: 1.8rem;\">OneClick Terms found around 600\u00a0terms<\/span><\/p><p style=\"margin-left: .5in;\">\u00a0<\/p><p><b>Q&amp;A from the audience<\/b><\/p><p>Q. How do you handle data privacy?<\/p><p>How are our highly confidential documents protected when<br \/>using this online tool? Are documents stored after processing? Do you have an<br \/>offline desktop version available?<\/p><p>\u00a0<\/p><p>A.The tool is exclusively online because it requires access<br \/>to 660 billion words of reference data that cannot be installed on individual<br \/>computers.<\/p><p>We have implemented the following data security measures:<\/p><ul style=\"margin-top: 0in;\" type=\"disc\"><li>Each user has their own\u00a0private account<\/li><li>Data is uploaded only to\u00a0the individual user&#8217;s account<\/li><li>No one else has access to\u00a0the uploaded data<\/li><li>The company doesn&#8217;t use\u00a0the data for any purpose<\/li><li>They don&#8217;t even want to\u00a0access the data because they don&#8217;t know what it contains<span style=\"text-indent: -0.25in; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; font-size-adjust: none; font-kerning: auto; font-optical-sizing: auto; font-feature-settings: normal; font-variation-settings: normal; font-variant-position: normal; font-variant-emoji: normal; font-stretch: normal; font-size: 7pt; line-height: normal; font-family: 'Times New Roman';\">\u00a0\u00a0<\/span><\/li><li>The company holds an ISO certificate for\u00a0<span style=\"text-indent: -0.25in; font-size: 1.8rem;\">Electronic Security.<\/span><\/li><\/ul><p>Q. Can you explain your pricing model?<\/p><p>A.We have a subscription model. If you are a freelancer, the<br \/>cost is 140 euros per year for 12 months. A monthly subscription is also<br \/>possible. If you are a language service provider, we offer a corporate<br \/>subscription. Its cost is determined on a case-by-case basis by the volume of<br \/>data you expect to upload.<\/p><p>\u00a0<\/p><p>Q. Do you offer a trial version of OneClick Terms?<\/p><p>A. Yes, you can sign-up for a 30-day trial.<\/p><p>\u00a0<\/p><p>Q. How can I get support with OneClick Terms?<\/p><p>A. You can click the \u201cRequest support\u201d button found at the<br \/>bottom of all pages. We offer live support from 9:00 am to 5:00 pm CET. We are<br \/>committed to responding to you within hours or the following workday. The<br \/>support team consists of trained linguists, computational linguists, and experts<br \/>in natural language processing. We are able to understand any linguistic<br \/>question in any language.<\/p><p>\u00a0<\/p><p>Q. What is the learning curve for using OneClick Terms? And<br \/>can a new user acquire the knowledge to use your tool in an optimal way?<\/p><p>A. The \u201cSTART HERE\u201d button is quite intuitive. The other<br \/>SketchEngine functionalities are a bit more complex. We have online tutorials<br \/>through our YouTube channel. The videos are short and concise. We also organize<br \/>face-to-face courses.<\/p><p>\u00a0<\/p><p>Q. Can I create my own corpus of \u201creference language\u201d before<br \/>starting a project, for example, choose texts that are exclusively written in<br \/>one specific Spanish language variant?<\/p><p>A. OneClick Terms supports all varieties of Spanish without<br \/>needing specific settings &#8211; it works universally across different Spanish variants.<br \/>For the full SketchEngine platform, users have two main options:<\/p><p>Pre-built Spanish corpus:<\/p><ul style=\"margin-top: 0in;\" type=\"disc\"><li>Contains 28 billion words of Spanish text<\/li><li>Already divided into regional subcorpora including Chilean, Colombian, Dominican, Ecuadorian, and others<\/li><li>Allows searches within specific regional variants<\/li><\/ul><p>Custom corpus creation: Users can build their own Spanish\u00a0corpus by:<\/p><ul style=\"margin-top: 0in;\" type=\"disc\"><li>Naming their corpus<\/li><li>Selecting Spanish as the\u00a0language<\/li><li>Gathering data from the\u00a0internet or uploading their own documents<\/li><li>Creating a corpus focused\u00a0on a specific Spanish variety if desired.<\/li><\/ul><p>Q. When building your general language corpus, do you have<br \/>access to content that is protected by passwords, for example media or<br \/>specialized publications?<\/p><p>A. No, our corpora are built on public information only.<\/p><p>\u00a0<\/p><p>Q. What kind of functionalities are you currently working on<br \/>developing?<\/p><p>A. A large share of our work consists in building new corpora with the latest data. We are also looking at expanding the number of supported languages.<\/p><div><p><!-- [if !supportAnnotations]--><\/p><div><div><p>For more details about this post, please visit\u00a0<a style=\"background-color: #ffffff; font-size: 1.8rem;\" href=\"https:\/\/terms.sketchengine.eu\/\">OneClickTerms<\/a>.<\/p><p><!-- [if !supportAnnotations]--><\/p><\/div><p><!--[endif]--><\/p><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c59a67d elementor-widget elementor-widget-text-editor\" data-id=\"c59a67d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Disclosure: Claude has been a contributor to this blog post.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>By Anne Chemali July 28, 2025 The ATA Language Technology Division (LTD) held its quarterly ATA TEKTalk on July 10, 2025, featuring Ond\u0159ej Matu\u0161ka, a linguist and the head of sales at SketchEngine, a corpus system developed by Lexical Computing, a company based in Brno, in Czech Republic. His role includes promoting the use of [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[11],"tags":[13],"class_list":{"0":"post-1278","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-ata-tektalks","7":"tag-ata-tektalks","8":"entry"},"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/pQoPc-kC","_links":{"self":[{"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/posts\/1278","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/comments?post=1278"}],"version-history":[{"count":4,"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/posts\/1278\/revisions"}],"predecessor-version":[{"id":1287,"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/posts\/1278\/revisions\/1287"}],"wp:attachment":[{"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/media?parent=1278"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/categories?post=1278"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ata-divisions.org\/LTD\/wp-json\/wp\/v2\/tags?post=1278"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}