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 Catalan UPOS tagging now.
| Group | Tag | Meaning | Example |
|---|---|---|---|
| Open Class | ADJ | Adjective | gran, vell, verd, incomprensible, primer |
| ADV | Adverb | molt, demà, avall, on, allà | |
| INTJ | Interjection | psst, ai, bravo, hola | |
| NOUN | Noun (common) | nena, gat, arbre, aire, bellesa | |
| PROPN | Proper Noun | Mary, John, Londres, OTAN, HBO | |
| VERB | Verb | corre, corre, corre, menja, menja, menja | |
| Closed Class | ADP | Adposition | a, a, durant |
| AUX | Auxiliary | és, ha (fet), ho farà, hauria de (fer) | |
| CONJ | Conjunction | i, o, però (etiqueta heretada) | |
| CCONJ | Coordinating Conjunction | i, o, però | |
| SCONJ | Subordinating Conjunction | si, mentre, això | |
| DET | Determiner | a, an, el | |
| NUM | Numeral | 1, 2017, un, setanta-set, MMXIV | |
| PART | Particle | , no | |
| PRON | Pronoun | Jo, tu, ell, ella, jo mateix, ells mateixos, algú | |
| 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 Catalan 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 menja. |
| csubj | Clausal subject | El que va fer estava malament. | |
| obj | Direct object | Veig la lluna. | |
| iobj | Indirect object | Ella em va fer un regal. | |
| ccomp | Clausal complement (finite) | Va dir que estava cansat. | |
| xcomp | Open clausal complement | Vull anar. | |
| Non-Core Dependents | obl | Oblique nominal | Es va asseure a la cadira. |
| vocative | Vocative | John, vine aquí! | |
| expl | Expletive | Hi un gat. | |
| dislocated | Dislocated element | Aquell home, el conec. | |
| advcl | Adverbial clause modifier | Vaig marxar després que va arribar. | |
| advmod | Adverbial modifier | Executar ràpid. | |
| discourse | Discourse element | Bé, no n'estic segur. | |
| aux | Auxiliary | Jo puc veure. | |
| cop | Copula | Ella està feliç. | |
| mark | Subordinating marker | Sé que ho saps. | |
| Nominal Dependents | nmod | Nominal modifier | La porta del cotxe. |
| appos | Appositional modifier | Sam, el meu amic. | |
| nummod | Numeric modifier | Set dies. | |
| acl | Adjectival clause | El pla guanyar. | |
| amod | Adjectival modifier | El cel blau. | |
| det | Determiner | El final. | |
| case | Case marking | El rei de França. | |
| fixed | Fixed multiword expression | Malgrat això. | |
| flat | Flat multiword name | Ciutat de Nova York. | |
| compound | Compound noun | Cabina de telèfon. | |
| list | List element | Telèfon, claus, cartera. | |
| Coordination | conj | Conjunct | Pa i mantega. |
| cc | Coordinating conjunction | Pa i mantega. | |
| Special Labels | aux:pass | Passive auxiliary | Va va ser robat. |
| punct | Punctuation | Hola! | |
| dep | Unspecified dependency | (S'utilitza per a enllaços desconeguts) | |
| ROOT | Root of the sentence | He menjat el dinar. |
| Attachment | Full Name | Explanation | Example |
|---|---|---|---|
| :pass | Passive | Indicates a relationship in a passive voice construction. | nsubj:pass (la finestra s'ha trencat) |
| :nn | Noun Compound | Indicates that a noun is modifying another noun in a compound structure. | compost:nn (carregador de telèfon) |
| :prep | Prepositional | Refines a modifier governed specifically by a preposition. | nmod:prep (El gat a la catifa) |
| :assmod | Associative Modifier | Common in Romanian/Baltic languages; shows nouns modifying other nouns. | nmod:assmod (El cotxe del meu pare) |
| :poss | Possessive | Indicates ownership or a possessive relationship. | nmod:poss (El meu gos, barret de Joan) |
| :relcl | Relative Clause | Identifies a clause that modifies a noun phrase. | acl:relcl (El llibre que vaig llegir) |
| :tmod | Temporal Modifier | A modifier specifically describing time or duration. | nmod:tmod (marto dimarts) |
| :prt | Particle | Used for phrasal verb particles. | compost:prt (Donar amunt, tancar apagar) |
| :rcomp | Relative Complement | Used for complements of relative clauses (common in Dutch). | advcl:rcomp (L'home que va marxar) |
| :flat | Flat Modifier | Used for multi-word expressions that don't have a clear internal head. | pla:nom (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) | EUA, Nova York, França, Califòrnia |
| 🏔️ LOC | Non-political location (mountains, rivers) | Oceà Pacífic, Everest, Alps |
| 🏢 FAC | Facility (buildings, airports, highways) | Golden Gate Bridge, aeroport JFK, Burj Khalifa |
| 👤 PERSON | People (real or fictional) | Elon Musk, Harry Potter, Alan Turing |
| 🚩 NORP | Nationalities, religious or political groups | Americà, budista, demòcrata, japonès |
| 🏢 ORG | Organizations (companies, institutions) | Google, Nacions Unides, Apple, FIFA |
| 📅 DATE | Absolute or relative dates | 4 de juliol de 2026, ahir, la setmana que ve |
| ⌚ TIME | Times smaller than a day | 9:30, posta de sol, deu minuts |
| 🎊 EVENT | Named events (wars, festivals) | Segona Guerra Mundial, Coachella, Jocs Olímpics |
| 💰 MONEY | Monetary values, including unit | 100 $, 5 milions d'euros, 50 £ |
| ‱ PERCENT | Percentage, including "%" | 20%, vuitanta per cent, 0,5% |
| ⚖️ QUANTITY | Measurements (weight, distance) | 5 km, 100 lliures, 30 metres quadrats |
| 🔢 ORDINAL | "First", "second", etc. | primer, 2n, novè |
| 🔢 CARDINAL | Numbers not classified elsewhere | 10, mil, tres |
| 📦 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 | La Constitució, Tractat de Versalles |
| 🗣️ LANGUAGE | Named languages | Anglès, Python, Mandarí |
Si processem la frase "Google té la seu a Califòrnia", les capes es veuen així:
Lema: "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" és el nsubj (subjecte nominal) del verb "basat" que és Arrel (Arrel de la frase).
NER: "Google" és una 🏢 ORG (organització), "Califòrnia" és una 🌍 GPE (Entitat geopolítica).
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