--- title: "DET: determiner — definition and key papers — Elamur Research" description: "DET (determiner) is the Universal Dependencies part-of-speech tag for words that modify a noun or noun phrase and fix its reference in…" canonical: "https://research.elamur.ai/free/en/concepts/upos-det/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/concepts/upos-det/) [home](https://md.research.elamur.ai/free/en/) / [concepts](https://md.research.elamur.ai/free/en/concepts/) / DET: determiner # 🏷️ DET: determiner Universal Dependencies · 7 key papers · [all concepts](https://md.research.elamur.ai/free/en/concepts/) Part of: [🗨️ Natural language processing](https://md.research.elamur.ai/free/en/concepts/natural-language-processing/) · [🌐 Universal Dependencies](https://md.research.elamur.ai/free/en/concepts/universal-dependencies/) DET (determiner) is the Universal Dependencies part-of-speech tag for words that modify a noun or noun phrase and fix its reference in context: articles, demonstratives, quantifiers and, in many languages, possessive and interrogative words that accompany a noun. Also: determiner, UPOS DET, det (its usual relation), article, quantifier ## What it is In [Universal Dependencies](https://md.research.elamur.ai/free/en/concepts/universal-dependencies/), every word gets one tag from a closed inventory of seventeen universal parts of speech ([Nivre et al. 2020](https://md.research.elamur.ai/free/en/papers/nivre-2020-universal-dependencies-v2-evergrowing-multilingual/)). DET is the tag for words that sit next to a noun and tell the hearer which or how many referents are meant. They do not add descriptive content. The word *the* in *the cat* does not describe the cat. It signals that the speaker expects the listener to identify it. The tag goes back to the twelve-category universal tagset of Petrov, Das and McDonald. That set already had DET beside NOUN, PRON, ADJ and NUM, and it was built by mapping many treebank-specific tagsets onto shared categories ([Petrov et al. 2012](https://md.research.elamur.ai/free/en/papers/petrov-2012-universal-part-speech-tagset/)). UD v1 extended that set to seventeen tags and kept DET unchanged ([Nivre et al. 2016](https://md.research.elamur.ai/free/en/papers/nivre-2016-universal-dependencies-v1-multilingual-treebank/)). UD treats determiners as function words. They depend on the content word they modify, which here is the noun ([Marneffe et al. 2021](https://md.research.elamur.ai/free/en/papers/marneffe-2021-universal-dependencies/)). Their typical relation is `det`. Some treebanks use subtypes such as `det:poss` or `det:predet`, since languages may refine universal relations but not invent new basic ones ([Nivre et al. 2020](https://md.research.elamur.ai/free/en/papers/nivre-2020-universal-dependencies-v2-evergrowing-multilingual/)). ### Borderline cases | Contrast | Typical decision | | --- | --- | | DET vs PRON | A word inside a noun phrase that modifies the noun is DET (*this book*). A form standing alone as an argument is often PRON (*I like this*), but practice varies by treebank. | | DET vs NUM | Cardinal numbers are NUM with `nummod`. Quantifiers like *many*, *some* and *every* are DET. | | DET vs ADJ | Words with descriptive content or full adjectival behaviour (*other*, *such* in some treebanks) may be ADJ. | | Possessives | English *my* and *your* are tagged PRON with Poss=Yes in the main treebanks. Many languages tag possessives as DET. | ### Features Determiners usually carry PronType, which says which kind they are: Art (article), Dem (demonstrative), Ind, Tot, Neg, Int or Rel. Articles also carry Definite (Def or Ind). Determiners in inflecting languages agree with their noun in Number, Gender and Case. Possessives carry Poss, Person and sometimes the possessor's number. This feature inventory descends from Interset, a universal set of morphosyntactic features designed as an interlingua between tagsets ([Zeman 2008](https://md.research.elamur.ai/free/en/papers/zeman-2008-reusable-tagset-conversion-tagset-drivers/)). ## Examples - English *the dog*, *a dog*, *every dog*, *which dog?*: each determiner is DET and attaches to *dog* by `det`. - English *all the dogs*: *all* is a predeterminer, attached as `det:predet` in some treebanks. - French *le chat*, *la maison*, *ces livres*, *mon ami*: articles, demonstratives and possessives are all DET and agree with the noun. - German *dem Mann*: the article marks dative case, singular, masculine. - Italian *del pane*: the partitive is a contraction of preposition plus article. It is split into ADP and DET in the annotation. ## Across languages Languages differ in how much they grammaticalize reference. English and the Romance languages have obligatory articles. Many Slavic languages have none, so their DET words are mostly demonstratives, quantifiers and possessives. Some languages mark definiteness with a suffix rather than a separate word, as Swedish *huset* ('the house') does. In such languages definiteness shows up as a feature on the NOUN and not as a DET token. UD splits contracted forms and clitics into syntactic words while keeping the original tokens recoverable ([Nivre et al. 2016](https://md.research.elamur.ai/free/en/papers/nivre-2016-universal-dependencies-v1-multilingual-treebank/)). French *du* ('of the') and similar fused forms therefore yield a DET token of their own. ## In treebanks and research In current UD releases, determiners make up a noticeably larger share of tokens in French than in English. This reflects the obligatory article of French, which appears even before plural and mass nouns. In both languages the relation `det` overwhelmingly dominates. The secondary relations show how the languages differ. In English, a DET word that stands alone as a phrase most often takes `nmod`, then `obj` and `nsubj`, as in *both* or *each* used on their own, with some `discourse` uses as well. In French, the next most common relations are `fixed`, for determiners frozen inside multiword expressions, then `advmod` and `reparandum`, the latter for self-corrections in spoken data. Because determiners are frequent and short, the DET versus PRON decision has a measurable effect on cross-treebank agreement. Work on annotation consistency in UD examines exactly such tag disagreements ([Marneffe et al. 2017](https://md.research.elamur.ai/free/en/papers/marneffe-2017-assessing-annotation-consistency-universal-dependencies/)). One proposal compares UPOS trigram distributions across treebanks of the same language with a symmetric divergence score, so that it does not rely on a trained tagger ([Aggarwal & Zeman 2020](https://md.research.elamur.ai/free/en/papers/aggarwal-2020-estimating-pos-annotation-consistency-different/)). For [part-of-speech tagging](https://md.research.elamur.ai/free/en/concepts/part-of-speech-tagging/) and [dependency parsing](https://md.research.elamur.ai/free/en/concepts/dependency-parsing/), the coarse DET class is part of why parsers can be transferred across languages. A delexicalized English parser using the universal tags transferred directly to other languages better than the unsupervised methods of its time ([Petrov et al. 2012](https://md.research.elamur.ai/free/en/papers/petrov-2012-universal-part-speech-tagset/)). Introductory accounts of UD's principles and tooling cover these tag choices for annotators (Zeman 2021). How often the tag DET occurs: its share of all tokens Counted by code over the Universal Dependencies 2.18 treebanks of English and French (every token once, subtypes with their base relation). **The numbers** | Treebanks | Share | | --- | --- | | English treebanks | 7.91% of tokens (89,135 tokens) | | French treebanks | 12.80% of tokens (139,556 tokens) | The relations DET words take most often The five most frequent in each language's treebanks, by tokens. **The numbers** | Pair | Tokens | | --- | --- | | English: det | 85,373 | | English: nmod | 848 | | English: obj | 612 | | English: nsubj | 556 | | English: discourse | 369 | | French: det | 138,049 | | French: fixed | 532 | | French: advmod | 353 | | French: reparandum | 329 | | French: obj | 74 | ## Key papers The works this page cites, the most cited first; citations as counted by OpenAlex plus the papers of this library that cite the work, read 2026-10-24. - [Universal Dependencies v1: A Multilingual Treebank Collection](https://md.research.elamur.ai/free/en/papers/nivre-2016-universal-dependencies-v1-multilingual-treebank/) — Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter et al. · 2016 · 1,741 citations - [A Universal Part-of-Speech Tagset](https://md.research.elamur.ai/free/en/papers/petrov-2012-universal-part-speech-tagset/) — Slav Petrov, Dipanjan Das, Ryan McDonald · 2012 · 1,180 citations - [Universal Dependencies](https://md.research.elamur.ai/free/en/papers/marneffe-2021-universal-dependencies/) — Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre et al. · 2021 · 480 citations - [Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection](https://md.research.elamur.ai/free/en/papers/nivre-2020-universal-dependencies-v2-evergrowing-multilingual/) — Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter et al. · 2020 · 325 citations - [Reusable Tagset Conversion Using Tagset Drivers](https://md.research.elamur.ai/free/en/papers/zeman-2008-reusable-tagset-conversion-tagset-drivers/) — Daniel Zeman · 2008 · 181 citations - [Assessing the Annotation Consistency of the Universal Dependencies Corpora](https://md.research.elamur.ai/free/en/papers/marneffe-2017-assessing-annotation-consistency-universal-dependencies/) — Marie-Catherine de Marneffe, Matias Grioni, Jenna Kanerva et al. · 2017 · 30 citations - [Estimating POS Annotation Consistency of Different Treebanks in a Language](https://md.research.elamur.ai/free/en/papers/aggarwal-2020-estimating-pos-annotation-consistency-different/) — Akshay Aggarwal, Daniel Zeman · 2020 · 7 citations ## Related concepts - [Universal Dependencies](https://md.research.elamur.ai/free/en/concepts/universal-dependencies/) — Universal Dependencies is a framework and an open collection of treebanks that annotates the grammar of many languages with one shared… - [Part-of-speech tagging](https://md.research.elamur.ai/free/en/concepts/part-of-speech-tagging/) — Part-of-speech tagging is the task of assigning each token in a text a grammatical category, such as noun, verb, adjective or determiner… - [Morphology](https://md.research.elamur.ai/free/en/concepts/morphology/) — Morphology is the branch of linguistics that studies the internal structure of words. It covers how words are built from meaningful units… ## More papers Topics: [🔤 Part-of-speech tagging](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/) · [🌐 Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) Shelves: [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) - [← previous concept det: determiner](https://md.research.elamur.ai/free/en/concepts/ud-det/) - [next concept → Discourse analysis](https://md.research.elamur.ai/free/en/concepts/discourse-analysis/) - [↑ back to concepts](https://md.research.elamur.ai/free/en/concepts/)