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class="firstHeading mw-first-heading"><span class="mw-page-title-main">Textual entailment</span></h1> <div id="p-lang-btn" class="vector-dropdown mw-portlet mw-portlet-lang" > <input type="checkbox" id="p-lang-btn-checkbox" role="button" aria-haspopup="true" data-event-name="ui.dropdown-p-lang-btn" class="vector-dropdown-checkbox mw-interlanguage-selector" aria-label="Go to an article in another language. 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class="vector-body" aria-labelledby="firstHeading" data-mw-ve-target-container> <div class="vector-body-before-content"> <div class="mw-indicators"> </div> <div id="siteSub" class="noprint">From Wikipedia, the free encyclopedia</div> </div> <div id="contentSub"><div id="mw-content-subtitle"></div></div> <div id="mw-content-text" class="mw-body-content"><div class="mw-content-ltr mw-parser-output" lang="en" dir="ltr"><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">Concept in natural language processing</div> <p>In <a href="/wiki/Natural_language_processing" title="Natural language processing">natural language processing</a>, <b>textual entailment</b> (<b>TE</b>), also known as <b>natural language inference</b> (<b>NLI</b>), is a directional relation between <a href="/wiki/Text_(literary_theory)" title="Text (literary theory)">text</a> fragments. The relation holds whenever the truth of one text fragment follows from another text. </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="Definition">Definition</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=1" title="Edit section: Definition"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>In the TE framework, the entailing and entailed texts are termed <i>text</i> (<i>t</i>) and <i>hypothesis</i> (<i>h</i>), respectively. Textual entailment is not the same as pure <a href="/wiki/Entailment" class="mw-redirect" title="Entailment">logical entailment</a> – it has a more relaxed definition: "<i>t</i> entails <i>h</i>" (<i>t</i> ⇒ <i>h</i>) if, typically, a human reading <i>t</i> would infer that <i>h</i> is most likely true.<sup id="cite_ref-1" class="reference"><a href="#cite_note-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> (Alternatively: <i>t</i> ⇒ <i>h</i> if and only if, typically, a human reading <i>t</i> would be justified in inferring the proposition expressed by <i>h</i> from the proposition expressed by <i>t</i>.<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup>) The relation is directional because even if "<i>t</i> entails <i>h</i>", the reverse "<i>h</i> entails <i>t</i>" is much less certain.<sup id="cite_ref-daga2004_3-0" class="reference"><a href="#cite_note-daga2004-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-tata_4-0" class="reference"><a href="#cite_note-tata-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p><p>Determining whether this relationship holds is an informal task, one which sometimes overlaps with the formal tasks of <a href="/wiki/Formal_semantics_(linguistics)" class="mw-redirect" title="Formal semantics (linguistics)">formal semantics</a> (satisfying a strict condition will usually imply satisfaction of a less strict conditioned); additionally, textual entailment partially subsumes <a href="/wiki/Entailment_(linguistics)" title="Entailment (linguistics)">word entailment</a>. </p> <div class="mw-heading mw-heading2"><h2 id="Examples">Examples</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=2" title="Edit section: Examples"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Textual entailment can be illustrated with examples of three different relations:<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> </p><p>An example of a <b>positive TE</b> (text entails hypothesis) is: </p> <ul><li>text: <i>If you help the needy, God will reward you</i>.</li></ul> <dl><dd>hypothesis: <i>Giving money to a poor man has good consequences</i>.</dd></dl> <p>An example of a <b>negative TE</b> (text contradicts hypothesis) is: </p> <ul><li>text: <i>If you help the needy, God will reward you</i>.</li></ul> <dl><dd>hypothesis: <i>Giving money to a poor man has no consequences</i>.</dd></dl> <p>An example of a <b>non-TE</b> (text does not entail nor contradict) is: </p> <ul><li>text: <i>If you help the needy, God will reward you</i>.</li></ul> <dl><dd>hypothesis: <i>Giving money to a poor man will make you a better person</i>.</dd></dl> <div class="mw-heading mw-heading2"><h2 id="Ambiguity_of_natural_language">Ambiguity of natural language</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=3" title="Edit section: Ambiguity of natural language"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>A characteristic of natural language is that there are many different ways to state what one wants to say: several meanings can be contained in a single text and the same meaning can be expressed by different texts. This variability of semantic expression can be seen as the dual problem of language <a href="/wiki/Semantic_ambiguity" title="Semantic ambiguity">ambiguity</a>. Together, they result in a <a href="/wiki/Many-to-many_(data_model)" title="Many-to-many (data model)">many-to-many</a> mapping between language expressions and meanings. The task of <a href="/wiki/Paraphrase" title="Paraphrase">paraphrasing</a> involves recognizing when two texts have the same meaning and creating a similar or shorter text that conveys almost the same information. Textual entailment is similar<sup id="cite_ref-Ion2009_6-0" class="reference"><a href="#cite_note-Ion2009-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup> but weakens the relationship to be unidirectional. Mathematical solutions to establish textual entailment can be based on the directional property of this relation, by making a comparison between some directional similarities of the texts involved.<sup id="cite_ref-tata_4-1" class="reference"><a href="#cite_note-tata-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Approaches">Approaches</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=4" title="Edit section: Approaches"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1251242444">.mw-parser-output .ambox{border:1px solid #a2a9b1;border-left:10px solid #36c;background-color:#fbfbfb;box-sizing:border-box}.mw-parser-output .ambox+link+.ambox,.mw-parser-output .ambox+link+style+.ambox,.mw-parser-output .ambox+link+link+.ambox,.mw-parser-output .ambox+.mw-empty-elt+link+.ambox,.mw-parser-output .ambox+.mw-empty-elt+link+style+.ambox,.mw-parser-output .ambox+.mw-empty-elt+link+link+.ambox{margin-top:-1px}html body.mediawiki .mw-parser-output .ambox.mbox-small-left{margin:4px 1em 4px 0;overflow:hidden;width:238px;border-collapse:collapse;font-size:88%;line-height:1.25em}.mw-parser-output .ambox-speedy{border-left:10px solid #b32424;background-color:#fee7e6}.mw-parser-output .ambox-delete{border-left:10px solid #b32424}.mw-parser-output .ambox-content{border-left:10px solid #f28500}.mw-parser-output .ambox-style{border-left:10px solid #fc3}.mw-parser-output .ambox-move{border-left:10px solid #9932cc}.mw-parser-output .ambox-protection{border-left:10px solid #a2a9b1}.mw-parser-output .ambox .mbox-text{border:none;padding:0.25em 0.5em;width:100%}.mw-parser-output .ambox .mbox-image{border:none;padding:2px 0 2px 0.5em;text-align:center}.mw-parser-output .ambox .mbox-imageright{border:none;padding:2px 0.5em 2px 0;text-align:center}.mw-parser-output .ambox .mbox-empty-cell{border:none;padding:0;width:1px}.mw-parser-output .ambox .mbox-image-div{width:52px}@media(min-width:720px){.mw-parser-output .ambox{margin:0 10%}}@media print{body.ns-0 .mw-parser-output .ambox{display:none!important}}</style><table class="box-Update plainlinks metadata ambox ambox-content ambox-Update" role="presentation"><tbody><tr><td class="mbox-image"><div class="mbox-image-div"><span typeof="mw:File"><span><img alt="" src="//upload.wikimedia.org/wikipedia/commons/thumb/9/98/Ambox_current_red.svg/42px-Ambox_current_red.svg.png" decoding="async" width="42" height="34" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/9/98/Ambox_current_red.svg/63px-Ambox_current_red.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/9/98/Ambox_current_red.svg/84px-Ambox_current_red.svg.png 2x" data-file-width="360" data-file-height="290" /></span></span></div></td><td class="mbox-text"><div class="mbox-text-span">This section needs to be <b>updated</b>.<span class="hide-when-compact"> Please help update this article to reflect recent events or newly available information.</span> <span class="date-container"><i>(<span class="date">November 2023</span>)</i></span></div></td></tr></tbody></table> <p>Textual entailment measures <a href="/wiki/Natural_language_understanding" title="Natural language understanding">natural language understanding</a> as it asks for a semantic interpretation of the text, and due to its generality remains an active area of research. Many approaches and refinements of approaches have been considered, such as <a href="/wiki/Word_embedding" title="Word embedding">word embedding</a>, logical models, graphical models, rule systems, contextual focusing, and machine learning.<sup id="cite_ref-Ion2009_6-1" class="reference"><a href="#cite_note-Ion2009-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup> Practical or large-scale solutions avoid these complex methods and instead use only surface syntax or lexical relationships, but are correspondingly less accurate.<sup id="cite_ref-daga2004_3-1" class="reference"><a href="#cite_note-daga2004-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> As of 2005<sup class="plainlinks noexcerpt noprint asof-tag update" style="display:none;"><a class="external text" href="https://en.wikipedia.org/w/index.php?title=Textual_entailment&action=edit">[update]</a></sup>, state-of-the-art systems are far from human performance; a study found humans to agree on the dataset 95.25% of the time.<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> Algorithms from 2016 had not yet achieved 90%.<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Applications">Applications</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=5" title="Edit section: Applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Many natural language processing applications, like <a href="/wiki/Question_answering" title="Question answering">question answering</a>, <a href="/wiki/Information_extraction" title="Information extraction">information extraction</a>, <a href="/wiki/Automatic_summarization" title="Automatic summarization">summarization</a>, <a href="/wiki/Multi-document_summarization" title="Multi-document summarization">multi-document</a> summarization, and <a href="/wiki/Evaluation_of_machine_translation" title="Evaluation of machine translation">evaluation of machine translation</a> systems, need to recognize that a particular target meaning can be inferred from different text variants. Typically entailment is used as part of a larger system, for example in a prediction system to filter out trivial or obvious predictions.<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> Textual entailment also has applications in <a href="/wiki/Adversarial_stylometry" title="Adversarial stylometry">adversarial stylometry</a>, which has the objective of removing textual style without changing the overall meaning of communication.<sup id="cite_ref-FOOTNOTEPotthastHagenStein201611-12_10-0" class="reference"><a href="#cite_note-FOOTNOTEPotthastHagenStein201611-12-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Datasets">Datasets</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=6" title="Edit section: Datasets"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Some of available English NLI datasets include: </p> <ul><li><a rel="nofollow" class="external text" href="https://nlp.stanford.edu/projects/snli/">SNLI</a><sup id="cite_ref-Bowman2015_11-0" class="reference"><a href="#cite_note-Bowman2015-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://cims.nyu.edu/~sbowman/multinli/">MultiNLI</a><sup id="cite_ref-Williams2018_12-0" class="reference"><a href="#cite_note-Williams2018-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://allenai.org/data/scitail">SciTail</a><sup id="cite_ref-Khot2018_13-0" class="reference"><a href="#cite_note-Khot2018-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://alt.qcri.org/semeval2014/task1/">SICK</a><sup id="cite_ref-Marelli2014_14-0" class="reference"><a href="#cite_note-Marelli2014-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://jgc128.github.io/mednli/">MedNLI</a><sup id="cite_ref-Romanov2018_15-0" class="reference"><a href="#cite_note-Romanov2018-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://github.com/kelvinguu/qanli">QA-NLI</a><sup id="cite_ref-Demszky2018_16-0" class="reference"><a href="#cite_note-Demszky2018-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup></li></ul> <p>In addition, there are several non-English NLI datasets, as follows: </p> <ul><li><a rel="nofollow" class="external text" href="https://cims.nyu.edu/~sbowman/xnli/">XNLI</a><sup id="cite_ref-Conneau2018_17-0" class="reference"><a href="#cite_note-Conneau2018-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://github.com/dml-qom/FarsTail">FarsTail</a><sup id="cite_ref-Amirkhani2021_18-0" class="reference"><a href="#cite_note-Amirkhani2021-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://github.com/CLUEbenchmark/OCNLI">OCNLI</a><sup id="cite_ref-Hu2020_19-0" class="reference"><a href="#cite_note-Hu2020-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://github.com/gijswijnholds/sick%20nl">SICK-NL</a><sup id="cite_ref-Wijnholds2021_20-0" class="reference"><a href="#cite_note-Wijnholds2021-20"><span class="cite-bracket">[</span>20<span class="cite-bracket">]</span></a></sup></li> <li><a rel="nofollow" class="external text" href="https://github.com/ir-nlp-csui/indonli">IndoNLI</a><sup id="cite_ref-Mahendra2021_21-0" class="reference"><a href="#cite_note-Mahendra2021-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup></li></ul> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=7" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Entailment_(linguistics)" title="Entailment (linguistics)">Entailment (linguistics)</a></li> <li><a href="/wiki/Inference_engine" title="Inference engine">Inference engine</a></li> <li><a href="/wiki/Semantic_reasoner" title="Semantic reasoner">Semantic reasoner</a></li> <li><a href="/wiki/Fuzzy_logic" title="Fuzzy logic">Fuzzy logic</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Textual_entailment&action=edit&section=8" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-references-wrap mw-references-columns"><ol class="references"> <li id="cite_note-1"><span class="mw-cite-backlink"><b><a href="#cite_ref-1">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external text" href="http://u.cs.biu.ac.il/~dagan/publications/RTEChallenge.pdf">Ido Dagan, Oren Glickman and Bernardo Magnini. The PASCAL Recognising Textual Entailment Challenge, p. 2</a> <a rel="nofollow" class="external text" href="https://web.archive.org/web/20120303215730/http://u.cs.biu.ac.il/~dagan/publications/RTEChallenge.pdf">Archived</a> 2012-03-03 at the <a href="/wiki/Wayback_Machine" title="Wayback Machine">Wayback Machine</a> <i>in:</i> Quiñonero-Candela, J.; Dagan, I.; Magnini, B.; d'Alché-Buc, F. (Eds.) <i>Machine Learning Challenges. Lecture Notes in Computer Science</i>, Vol. 3944, pp. 177–190, Springer, 2006.</span> </li> <li id="cite_note-2"><span class="mw-cite-backlink"><b><a href="#cite_ref-2">^</a></b></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}</style><cite id="CITEREFKormanMackJettRenear2018" class="citation journal cs1">Korman, Daniel Z.; Mack, Eric; Jett, Jacob; Renear, Allen H. (2018-03-09). <a rel="nofollow" class="external text" href="https://philpapers.org/rec/KORDTE">"Defining textual entailment"</a>. <i>Journal of the Association for Information Science and Technology</i>. <b>69</b> (6): 763–772. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1002%2Fasi.24007">10.1002/asi.24007</a>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/2330-1635">2330-1635</a>. <a href="/wiki/S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:46920779">46920779</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Journal+of+the+Association+for+Information+Science+and+Technology&rft.atitle=Defining+textual+entailment&rft.volume=69&rft.issue=6&rft.pages=763-772&rft.date=2018-03-09&rft_id=https%3A%2F%2Fapi.semanticscholar.org%2FCorpusID%3A46920779%23id-name%3DS2CID&rft.issn=2330-1635&rft_id=info%3Adoi%2F10.1002%2Fasi.24007&rft.aulast=Korman&rft.aufirst=Daniel+Z.&rft.au=Mack%2C+Eric&rft.au=Jett%2C+Jacob&rft.au=Renear%2C+Allen+H.&rft_id=https%3A%2F%2Fphilpapers.org%2Frec%2FKORDTE&rfr_id=info%3Asid%2Fen.wikipedia.org%3ATextual+entailment" class="Z3988"></span></span> </li> <li id="cite_note-daga2004-3"><span class="mw-cite-backlink">^ <a href="#cite_ref-daga2004_3-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-daga2004_3-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><a rel="nofollow" class="external text" href="http://u.cs.biu.ac.il/~dagan/publications/ProbabilisticTE_fv07.pdf">Dagan, I. and O. Glickman. 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language processing">Natural language processing</a></div></th></tr><tr><th scope="row" class="navbox-group" style="width:1%">General terms</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/AI-complete" title="AI-complete">AI-complete</a></li> <li><a href="/wiki/Bag-of-words_model" title="Bag-of-words model">Bag-of-words</a></li> <li><a href="/wiki/N-gram" title="N-gram">n-gram</a> <ul><li><a href="/wiki/Bigram" title="Bigram">Bigram</a></li> <li><a href="/wiki/Trigram" title="Trigram">Trigram</a></li></ul></li> <li><a href="/wiki/Computational_linguistics" title="Computational linguistics">Computational linguistics</a></li> <li><a href="/wiki/Natural_language_understanding" title="Natural language understanding">Natural language understanding</a></li> <li><a href="/wiki/Stop_word" title="Stop word">Stop words</a></li> <li><a href="/wiki/Text_processing" title="Text processing">Text processing</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Text_mining" title="Text mining">Text analysis</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Argument_mining" title="Argument mining">Argument mining</a></li> <li><a href="/wiki/Collocation_extraction" title="Collocation extraction">Collocation extraction</a></li> <li><a href="/wiki/Concept_mining" title="Concept mining">Concept mining</a></li> <li><a href="/wiki/Coreference#Coreference_resolution" title="Coreference">Coreference resolution</a></li> <li><a href="/wiki/Deep_linguistic_processing" title="Deep linguistic processing">Deep linguistic processing</a></li> <li><a href="/wiki/Distant_reading" title="Distant reading">Distant reading</a></li> <li><a href="/wiki/Information_extraction" title="Information extraction">Information extraction</a></li> <li><a href="/wiki/Named-entity_recognition" title="Named-entity recognition">Named-entity recognition</a></li> <li><a href="/wiki/Ontology_learning" title="Ontology learning">Ontology learning</a></li> <li><a href="/wiki/Parsing" title="Parsing">Parsing</a> <ul><li><a href="/wiki/Semantic_parsing" title="Semantic parsing">Semantic parsing</a></li> <li><a href="/wiki/Syntactic_parsing_(computational_linguistics)" title="Syntactic parsing (computational linguistics)">Syntactic parsing</a></li></ul></li> <li><a href="/wiki/Part-of-speech_tagging" title="Part-of-speech tagging">Part-of-speech tagging</a></li> <li><a href="/wiki/Semantic_analysis_(machine_learning)" title="Semantic analysis (machine learning)">Semantic analysis</a></li> <li><a href="/wiki/Semantic_role_labeling" title="Semantic role labeling">Semantic role labeling</a></li> <li><a href="/wiki/Semantic_decomposition_(natural_language_processing)" title="Semantic decomposition (natural language processing)">Semantic decomposition</a></li> <li><a href="/wiki/Semantic_similarity" title="Semantic similarity">Semantic similarity</a></li> <li><a href="/wiki/Sentiment_analysis" title="Sentiment analysis">Sentiment analysis</a></li></ul> <ul><li><a href="/wiki/Terminology_extraction" title="Terminology extraction">Terminology extraction</a></li> <li><a href="/wiki/Text_mining" title="Text mining">Text mining</a></li> <li><a class="mw-selflink selflink">Textual entailment</a></li> <li><a href="/wiki/Truecasing" title="Truecasing">Truecasing</a></li> <li><a href="/wiki/Word-sense_disambiguation" title="Word-sense disambiguation">Word-sense disambiguation</a></li> <li><a href="/wiki/Word-sense_induction" title="Word-sense induction">Word-sense induction</a></li></ul> </div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th id="Text_segmentation" scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Text_segmentation" title="Text segmentation">Text segmentation</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Compound-term_processing" title="Compound-term processing">Compound-term processing</a></li> <li><a href="/wiki/Lemmatisation" class="mw-redirect" title="Lemmatisation">Lemmatisation</a></li> <li><a href="/wiki/Lexical_analysis" title="Lexical analysis">Lexical analysis</a></li> <li><a href="/wiki/Shallow_parsing" title="Shallow parsing">Text chunking</a></li> <li><a href="/wiki/Stemming" title="Stemming">Stemming</a></li> <li><a href="/wiki/Sentence_boundary_disambiguation" title="Sentence boundary disambiguation">Sentence segmentation</a></li> <li><a href="/wiki/Word#Word_boundaries" title="Word">Word segmentation</a></li></ul> </div></td></tr></tbody></table><div> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Automatic_summarization" title="Automatic summarization">Automatic summarization</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Multi-document_summarization" title="Multi-document summarization">Multi-document summarization</a></li> <li><a href="/wiki/Sentence_extraction" title="Sentence extraction">Sentence extraction</a></li> <li><a href="/wiki/Text_simplification" title="Text simplification">Text simplification</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Machine_translation" title="Machine translation">Machine translation</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Computer-assisted_translation" title="Computer-assisted translation">Computer-assisted</a></li> <li><a href="/wiki/Example-based_machine_translation" title="Example-based machine translation">Example-based</a></li> <li><a href="/wiki/Rule-based_machine_translation" title="Rule-based machine translation">Rule-based</a></li> <li><a href="/wiki/Statistical_machine_translation" title="Statistical machine translation">Statistical</a></li> <li><a href="/wiki/Transfer-based_machine_translation" title="Transfer-based machine translation">Transfer-based</a></li> <li><a href="/wiki/Neural_machine_translation" title="Neural machine translation">Neural</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Distributional_semantics" title="Distributional semantics">Distributional semantics</a> models</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/BERT_(language_model)" title="BERT (language model)">BERT</a></li> <li><a href="/wiki/Document-term_matrix" title="Document-term matrix">Document-term matrix</a></li> <li><a href="/wiki/Explicit_semantic_analysis" title="Explicit semantic analysis">Explicit semantic analysis</a></li> <li><a href="/wiki/FastText" title="FastText">fastText</a></li> <li><a href="/wiki/GloVe" title="GloVe">GloVe</a></li> <li><a href="/wiki/Language_model" title="Language model">Language model</a> (<a href="/wiki/Large_language_model" title="Large language model">large</a>)</li> <li><a href="/wiki/Latent_semantic_analysis" title="Latent semantic analysis">Latent semantic analysis</a></li> <li><a href="/wiki/Seq2seq" title="Seq2seq">Seq2seq</a></li> <li><a href="/wiki/Word_embedding" title="Word embedding">Word embedding</a></li> <li><a href="/wiki/Word2vec" title="Word2vec">Word2vec</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Language_resource" title="Language resource">Language resources</a>,<br />datasets and corpora</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Types and<br />standards</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Corpus_linguistics" title="Corpus linguistics">Corpus linguistics</a></li> <li><a href="/wiki/Lexical_resource" title="Lexical resource">Lexical resource</a></li> <li><a href="/wiki/Linguistic_Linked_Open_Data" title="Linguistic Linked Open Data">Linguistic Linked Open Data</a></li> <li><a href="/wiki/Machine-readable_dictionary" title="Machine-readable dictionary">Machine-readable dictionary</a></li> <li><a href="/wiki/Parallel_text" title="Parallel text">Parallel text</a></li> <li><a href="/wiki/PropBank" title="PropBank">PropBank</a></li> <li><a href="/wiki/Semantic_network" title="Semantic network">Semantic network</a></li> <li><a href="/wiki/Simple_Knowledge_Organization_System" title="Simple Knowledge Organization System">Simple Knowledge Organization System</a></li> <li><a href="/wiki/Speech_corpus" title="Speech corpus">Speech corpus</a></li> <li><a href="/wiki/Text_corpus" title="Text corpus">Text corpus</a></li> <li><a href="/wiki/Thesaurus_(information_retrieval)" title="Thesaurus (information retrieval)">Thesaurus (information retrieval)</a></li> <li><a href="/wiki/Treebank" title="Treebank">Treebank</a></li> <li><a href="/wiki/Universal_Dependencies" title="Universal Dependencies">Universal Dependencies</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Data</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/BabelNet" title="BabelNet">BabelNet</a></li> <li><a href="/wiki/Bank_of_English" title="Bank of English">Bank of English</a></li> <li><a href="/wiki/DBpedia" title="DBpedia">DBpedia</a></li> <li><a href="/wiki/FrameNet" title="FrameNet">FrameNet</a></li> <li><a href="/wiki/Google_Ngram_Viewer" class="mw-redirect" title="Google Ngram Viewer">Google Ngram Viewer</a></li> <li><a href="/wiki/UBY" title="UBY">UBY</a></li> <li><a href="/wiki/WordNet" title="WordNet">WordNet</a></li> <li><a href="/wiki/Wikidata" title="Wikidata">Wikidata</a></li></ul> </div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Automatic_identification_and_data_capture" title="Automatic identification and data capture">Automatic identification<br />and data capture</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Speech_recognition" title="Speech recognition">Speech recognition</a></li> <li><a href="/wiki/Speech_segmentation" title="Speech segmentation">Speech segmentation</a></li> <li><a href="/wiki/Speech_synthesis" title="Speech synthesis">Speech synthesis</a></li> <li><a href="/wiki/Natural_language_generation" title="Natural language generation">Natural language generation</a></li> <li><a href="/wiki/Optical_character_recognition" title="Optical character recognition">Optical character recognition</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Topic_model" title="Topic model">Topic model</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Document_classification" title="Document classification">Document classification</a></li> <li><a href="/wiki/Latent_Dirichlet_allocation" title="Latent Dirichlet allocation">Latent Dirichlet allocation</a></li> <li><a href="/wiki/Pachinko_allocation" title="Pachinko allocation">Pachinko allocation</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Computer-assisted_reviewing" title="Computer-assisted reviewing">Computer-assisted<br />reviewing</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Automated_essay_scoring" title="Automated essay scoring">Automated essay scoring</a></li> <li><a href="/wiki/Concordancer" title="Concordancer">Concordancer</a></li> <li><a href="/wiki/Grammar_checker" title="Grammar checker">Grammar checker</a></li> <li><a href="/wiki/Predictive_text" title="Predictive text">Predictive text</a></li> <li><a href="/wiki/Pronunciation_assessment" title="Pronunciation assessment">Pronunciation assessment</a></li> <li><a href="/wiki/Spell_checker" title="Spell checker">Spell checker</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Natural-language_user_interface" title="Natural-language user interface">Natural language<br />user interface</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Chatbot" title="Chatbot">Chatbot</a></li> <li><a href="/wiki/Interactive_fiction" title="Interactive fiction">Interactive fiction</a> (c.f. <a href="/wiki/Syntax_guessing" class="mw-redirect" title="Syntax guessing">Syntax guessing</a>)</li> <li><a href="/wiki/Question_answering" title="Question answering">Question answering</a></li> <li><a href="/wiki/Virtual_assistant" title="Virtual assistant">Virtual assistant</a></li> <li><a href="/wiki/Voice_user_interface" title="Voice user interface">Voice user interface</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Related</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Formal_semantics_(natural_language)" title="Formal semantics (natural language)">Formal semantics</a></li> <li><a href="/wiki/Hallucination_(artificial_intelligence)" title="Hallucination (artificial intelligence)">Hallucination</a></li> <li><a href="/wiki/Natural_Language_Toolkit" title="Natural Language Toolkit">Natural Language Toolkit</a></li> <li><a href="/wiki/SpaCy" title="SpaCy">spaCy</a></li></ul> </div></td></tr></tbody></table></div>    </div><noscript><img src="https://login.wikimedia.org/wiki/Special:CentralAutoLogin/start?type=1x1" alt="" width="1" height="1" style="border: none; position: absolute;"></noscript> <div class="printfooter" data-nosnippet="">Retrieved from "<a dir="ltr" href="https://en.wikipedia.org/w/index.php?title=Textual_entailment&oldid=1217119091">https://en.wikipedia.org/w/index.php?title=Textual_entailment&oldid=1217119091</a>"</div></div> <div id="catlinks" class="catlinks" data-mw="interface"><div id="mw-normal-catlinks" class="mw-normal-catlinks"><a href="/wiki/Help:Category" title="Help:Category">Categories</a>: <ul><li><a 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