UPOS (Universal Part-of-Speech) tags are a core component of the Universal Dependencies (UD) project, designed to provide a standardized, fixed set of 17 categories that remain consistent across all human languages. Unlike language-specific systems (XPOS), which reflect the unique morphological intricacies of a single tongue, UPOS focuses on the functional role of a word. By stripping away language-specific "noise," UPOS allows researchers and developers to compare syntactic structures cross-linguistically and facilitates Cross-Lingual Transfer Learning—where an AI model trained on one language (like English) can apply its structural knowledge to another (like Romanian or Korean). It essentially serves as a "Lingua Franca" for computational linguistics, ensuring that a NOUN remains a NOUN whether the underlying grammar is agglutinative, fusional, or analytic.
Try our Norwegian UPOS tagging now.
| Group | Tag | Meaning | Example |
|---|---|---|---|
| Open Class | ADJ | Adjective | stor, gammel, grønn, uforståelig, først |
| ADV | Adverb | veldig, i morgen, nede, hvor, der | |
| INTJ | Interjection | psst, ouch, bravo, hei | |
| NOUN | Noun (common) | jente, katt, tre, luft, skjønnhet | |
| PROPN | Proper Noun | Mary, John, London, NATO, HBO | |
| VERB | Verb | løp, løp, løp, spis, spiste, spiste | |
| Closed Class | ADP | Adposition | i, til, under |
| AUX | Auxiliary | er, har (gjort), vil (gjøre), bør (gjøre) | |
| CONJ | Conjunction | og, eller, men (eldre tag) | |
| CCONJ | Coordinating Conjunction | og, eller, men | |
| SCONJ | Subordinating Conjunction | hvis, mens, det | |
| DET | Determiner | en, en, den | |
| NUM | Numeral | 1, 2017, en, syttisju, MMXIV | |
| PART | Particle | s, ikke | |
| PRON | Pronoun | Jeg, du, han, hun, meg selv, seg selv, noen | |
| Other | PUNCT | Punctuation | ., (, ), ?, ] |
| SYM | Symbol | $, %, +, −, :), 🐻 | |
| X | Other / Foreign | sfpksdpsxmsa, ..., foreign words | |
| SPACE | Space | newlines, tabs, extra spaces |
XPOS (Language-Specific Part-of-Speech) tagging offers a much higher level of granularity than the broader UPOS (Universal Part-of-Speech) system. While UPOS provides a standardized set of labels designed to work consistently across every language—ensuring that a NOUN in English is treated similarly to a NOUN in XPOS preserves the unique "linguistic DNA" of a specific language. It is the engine behind complex morphological analysis, allowing a system to distinguish not just that a word is a "Verb," but specifically that it is a "Third-Person, Singular, Past Tense, Passive Voice" verb. By capturing the deep grammatical details that UPOS omits for the sake of universality, XPOS enables the creation of translation tools and parsers that understand the precise inflectional logic of a specific culture and tongue.
In French, Spanish, Portuguese, Danish, Norwegian, Russian, Hebrew, Catalan, Finnish, Sanskrit, Thai and Ukrainian, a separate fine-grained XPOS tagset is not defined. Instead, these languages utilize UPOS with specific granularities stored within Morphological Features.
Try our Norwegian XPOS tagging now.
| Group | Category | Label | Meaning | Example |
|---|---|---|---|---|
| Nominal | Gender & Animacy | Masc | Masculine | perro (dog) |
| Fem | Feminine | perra (female dog) | ||
| Neut | Neuter | ello (it/that) | ||
| Com | Common | estudiante | ||
| Hum | Human | persona, qui | ||
| Anim | Animate | (Living entity) | ||
| Inan | Inanimate | (Object) | ||
| Definite & Degree | Def | Definite | le, la, el | |
| Ind | Indefinite | un, une | ||
| Pos | Positive degree | bueno, bon | ||
| Cmp | Comparative | más, plus | ||
| Sup | Superlative | buenísimo | ||
| Nominal | Number | Sing | Singular | livre (book) |
| Plur | Plural | livres (books) | ||
| Nominal | Case | Nom | Nominative | yo, I |
| Acc | Accusative | me, lo | ||
| Dat | Dative | le, me | ||
| Gen | Genitive | (Possessive case) | ||
| Nominal | NounType & NameType | Class | Classifier (NounType) | ตัว (body/animal) |
| Giv | Given Name (NameType) | สมชาย (Somchai) | ||
| Sur | Surname (NameType) | ใจดี (Jaidee) | ||
| Geo | Geographical (NameType) | กรุงเทพฯ (Bangkok) | ||
| Nat | Nationality (NameType) | ไทย (Thai) | ||
| Com | Company (NameType) | กูเกิล (Google) | ||
| Verbal | Mood & Aspect | Ind | Indicative | yo hablo |
| Sub | Subjunctive | que yo hable | ||
| Imp | Imperative | ¡habla! | ||
| Cnd | Conditional | hablaría | ||
| Imp | Imperfective | hablaba | ||
| Perf | Perfective | hablé | ||
| Prog | Progressive | estoy hablando | ||
| Verbal | Person & Politeness | 1 | First Person | yo, nosotros |
| 2 | Second Person | tú, vosotros | ||
| 3 | Third Person | él, ella | ||
| Form | Polite/Formal | Usted, Vous | ||
| Infm | Informal | tú, toi | ||
| Verbal | Tense | Pres | Present | mange, eat |
| Past | Past | mangé, ate | ||
| Fut | Future | mangerai | ||
| Verbal | VerbForm & Voice | Fin | Finite | il court |
| Inf | Infinitive | courir, to run | ||
| Part | Participle | vu, visto | ||
| Ger | Gerund | corriendo | ||
| Act | Active Voice | veo (I see) | ||
| Pass | Passive Voice | soy visto | ||
| Lexical | NumType | Card | Cardinal | uno, deux |
| Ord | Ordinal | primero, 1er | ||
| Mult | Multiplicative | doble, triple | ||
| PronType | Prs | Personal | yo, je | |
| Dem | Demonstrative | este, celui | ||
| Rel | Relative | que, qui | ||
| Int | Interrogative | ¿quién?, qui? | ||
| Lexical | Polarity & Poss | Neg | Negative | no, pas |
| Yes | Possessive | mio, sien | ||
| Yes | Reflexive | se, me, te | ||
| Lexical | PartType (Particles) | Enp | Ending Particle | ครับ (krab), ค่ะ (kha) |
| Res | Response Particle | ใช่ (chai / yes) | ||
| Int | Interrogative Particle | ไหม (mai / ?) | ||
| Special | Other | Yes | Foreign Word | software, ad-hoc |
| Yes | Abbreviation | etc., adj. | ||
| Special | Word Formation | Yes (Prefix) | Nominalizing Prefix | การ- (kan-), ความ- (khwam-) |
| Rdp (Echo) | Reduplicative | เด็กๆ (dek-dek) |
The DEP (Syntactic Dependency) refers to the specific grammatical relationship between a "child" token and its "head" (parent) token. While primary labels (like nsubj or obj) describe the basic structure, attachments starting with a colon (:) provide fine-grained sub-type information. For instance, while nsubj identifies a subject, :pass refines this to show the subject is being acted upon (Passive Voice). Similarly, :nn (Noun Compound) or :assmod (Associative Modifier) help the parser distinguish between simple modifiers and complex ownership or compound relationships, allowing for a much deeper "logical" understanding of the sentence.
| Category | Label | Meaning | Example (Token in bold) |
|---|---|---|---|
| Core Arguments | nsubj | Nominal subject | Elon spiser. |
| csubj | Clausal subject | Det han gjorde var feil. | |
| obj | Direct object | Jeg ser månen. | |
| iobj | Indirect object | Hun ga meg en gave. | |
| ccomp | Clausal complement (finite) | Han sa at han var sliten. | |
| xcomp | Open clausal complement | Jeg vil gå. | |
| Non-Core Dependents | obl | Oblique nominal | Han satt på stolen. |
| vocative | Vocative | John, kom hit! | |
| expl | Expletive | Det er en katt. | |
| dislocated | Dislocated element | Den mannen, jeg kjenner ham. | |
| advcl | Adverbial clause modifier | Jeg dro etter at han kom. | |
| advmod | Adverbial modifier | Løp raskt. | |
| discourse | Discourse element | Vel, jeg er ikke sikker. | |
| aux | Auxiliary | Jeg kan se. | |
| cop | Copula | Hun er glad. | |
| mark | Subordinating marker | Jeg vet at du vet. | |
| Nominal Dependents | nmod | Nominal modifier | bildøren. |
| appos | Appositional modifier | Sam, min venn. | |
| nummod | Numeric modifier | Syv dager. | |
| acl | Adjectival clause | Planen å vinne. | |
| amod | Adjectival modifier | Den blå himmelen. | |
| det | Determiner | Slutten. | |
| case | Case marking | Kongen av Frankrike. | |
| fixed | Fixed multiword expression | Til tross for det. | |
| flat | Flat multiword name | New York City. | |
| compound | Compound noun | Telefon. | |
| list | List element | Telefon, nøkler, lommebok. | |
| Coordination | conj | Conjunct | Brød og smør. |
| cc | Coordinating conjunction | Brød og smør. | |
| Special Labels | aux:pass | Passive auxiliary | Den ble stjålet. |
| punct | Punctuation | Hei! | |
| dep | Unspecified dependency | (Brukes for ukjente lenker) | |
| ROOT | Root of the sentence | Jeg spiste lunsj. |
| Attachment | Full Name | Explanation | Example |
|---|---|---|---|
| :pass | Passive | Indicates a relationship in a passive voice construction. | nsubj:pass (vinduet ble ødelagt) |
| :nn | Noun Compound | Indicates that a noun is modifying another noun in a compound structure. | sammensatt:nn (telefonlader) |
| :prep | Prepositional | Refines a modifier governed specifically by a preposition. | nmod:prep (Katten på matten) |
| :assmod | Associative Modifier | Common in Romanian/Baltic languages; shows nouns modifying other nouns. | nmod:assmod (Bilen til min far) |
| :poss | Possessive | Indicates ownership or a possessive relationship. | nmod:poss (Min hund, Johns hatt) |
| :relcl | Relative Clause | Identifies a clause that modifies a noun phrase. | acl:relcl (boken som jeg leste) |
| :tmod | Temporal Modifier | A modifier specifically describing time or duration. | nmod:tmod (jeg reiser tirsdag) |
| :prt | Particle | Used for phrasal verb particles. | sammensatt:prt (gi opp, slå av) |
| :rcomp | Relative Complement | Used for complements of relative clauses (common in Dutch). | advcl:rcomp (mannen som dro) |
| :flat | Flat Modifier | Used for multi-word expressions that don't have a clear internal head. | flat:name (President Obama) |
NER (Named Entity Recognition) is a Natural Language Processing (NLP) task that automatically identifies and categorizes key information (entities) in a text into predefined classes. In spaCy, the statistical model "looks" at the context of a word to determine if it refers to a person, an organization, a monetary value, or a specific date. This is crucial for extracting structured data from unstructured text, such as finding all the company names mentioned in a news article or identifying the dates of events in a history book.
Comparison Note: GPE vs. LOC
Determining whether a place is a GPE or a LOC depends on its political nature:
GPE (Geopolitical Entity): If the location has a government, specific laws, or human-defined administrative borders, it is labeled as a GPE. Examples include Seoul, Germany, the United Kingdom, and California.
LOC (Location): If the place is a natural physical feature or a broad geographic region without a singular governing body, it is labeled as a LOC. Examples include the Alps, the Pacific Ocean, the Middle East, and Mount Everest.
| Label | Meaning | Example |
|---|---|---|
| 🌍 GPE | Geopolitical entity (countries, cities, states) | USA, New York, Frankrike, California |
| 🏔️ LOC | Non-political location (mountains, rivers) | Stillehavet, Mount Everest, Alpene |
| 🏢 FAC | Facility (buildings, airports, highways) | Golden Gate Bridge, JFK flyplass, Burj Khalifa |
| 👤 PERSON | People (real or fictional) | Elon Musk, Harry Potter, Alan Turing |
| 🚩 NORP | Nationalities, religious or political groups | Amerikansk, buddhist, demokrat, japansk |
| 🏢 ORG | Organizations (companies, institutions) | Google, FN, Apple, FIFA |
| 📅 DATE | Absolute or relative dates | 4. juli 2026, i går, neste uke |
| ⌚ TIME | Times smaller than a day | 9:30, solnedgang, ti minutter |
| 🎊 EVENT | Named events (wars, festivals) | Andre verdenskrig, Coachella, olympiske leker |
| 💰 MONEY | Monetary values, including unit | $100, 5 millioner Euro, £50 |
| ‱ PERCENT | Percentage, including "%" | 20 %, åtti prosent, 0,5 % |
| ⚖️ QUANTITY | Measurements (weight, distance) | 5 km, 100 lbs, 30 kvadratmeter |
| 🔢 ORDINAL | "First", "second", etc. | første, andre, niende |
| 🔢 CARDINAL | Numbers not classified elsewhere | 10, ett tusen, tre |
| 📦 PRODUCT | Objects, vehicles, foods, etc. (not services) | iPhone, Tesla Model S, Coca-Cola |
| 🎨 WORK_OF_ART | Titles of books, songs, etc. | Mona Lisa, Bohemian Rhapsody, Hamlet |
| 📜 LAW | Named legal documents | Grunnloven, Versailles-traktaten |
| 🗣️ LANGUAGE | Named languages | Engelsk, Python, Mandarin |
Hvis vi behandler uttrykket «Google er basert i California», ser lagene slik ut:
Lemma: "Google", "be", "base", "in", "California"
UPOS: "PROPN(Proper Noun)", "AUX(Auxiliary)", "VERB(Verb)", "ADP(Adposition)", "PROPN(Proper Noun)"
XPOS: "NNP(Proper noun, singular)", "VBZ(Verb, 3rd person singular present)", "VBN(Verb, past participle)", "IN(Preposition or subordinating conjunction)", "NNP(Proper noun, singular)"
DEP: "Google" er nsubj (nominelt subjekt) til verbet "basert" som er Root (roten til setningen).
NER: «Google» er en 🏢 ORG (organisasjon), «California» er en 🌍 GPE (geopolitisk enhet).
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