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 Portuguese UPOS tagging now.
| Group | Tag | Meaning | Example |
|---|---|---|---|
| Open Class | ADJ | Adjective | grande, velho, verde, incompreensível, primeiro |
| ADV | Adverb | muito, amanhã, embaixo, onde, ali | |
| INTJ | Interjection | psst, ai, bravo, olá | |
| NOUN | Noun (common) | menina, gato, árvore, ar, beleza | |
| PROPN | Proper Noun | Mary, John, Londres, OTAN, HBO | |
| VERB | Verb | corre, corre, corre, come, comeu, comeu | |
| Closed Class | ADP | Adposition | dentro, para, durante |
| AUX | Auxiliary | é, tem (feito), irá (fazer), deveria (fazer) | |
| CONJ | Conjunction | e, ou, mas (tag herdada) | |
| CCONJ | Coordinating Conjunction | e, ou, mas | |
| SCONJ | Subordinating Conjunction | se, enquanto, isso | |
| DET | Determiner | um, um, o | |
| NUM | Numeral | 1º de janeiro de 2017, um, setenta e sete, MMXIV | |
| PART | Particle | de, não | |
| PRON | Pronoun | Eu, você, ele, ela, eu mesmo, eles mesmos, alguém | |
| 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 Portuguese 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 come. |
| csubj | Clausal subject | O que ele fez foi errado. | |
| obj | Direct object | Vejo a lua. | |
| iobj | Indirect object | Ela me me deu um presente. | |
| ccomp | Clausal complement (finite) | Ele disse que estava cansado. | |
| xcomp | Open clausal complement | Quero ir. | |
| Non-Core Dependents | obl | Oblique nominal | Ele sentou na cadeira. |
| vocative | Vocative | João, venha aqui! | |
| expl | Expletive | Há um gato. | |
| dislocated | Dislocated element | Esse homem, eu o conheço. | |
| advcl | Adverbial clause modifier | Saí depois que ele chegou. | |
| advmod | Adverbial modifier | Corra rápido. | |
| discourse | Discourse element | Bem, não tenho certeza. | |
| aux | Auxiliary | Eu posso ver. | |
| cop | Copula | Ela está feliz. | |
| mark | Subordinating marker | Eu sei que você sabe. | |
| Nominal Dependents | nmod | Nominal modifier | A porta do carro. |
| appos | Appositional modifier | Sam, meu amigo. | |
| nummod | Numeric modifier | Sete dias. | |
| acl | Adjectival clause | O plano para vencer. | |
| amod | Adjectival modifier | O céu azul. | |
| det | Determiner | O fim. | |
| case | Case marking | O rei da França. | |
| fixed | Fixed multiword expression | Apesar disso. | |
| flat | Flat multiword name | Nova York. | |
| compound | Compound noun | Cabinetelefone. | |
| list | List element | Telefone, chaves, carteira. | |
| Coordination | conj | Conjunct | Pão e manteiga. |
| cc | Coordinating conjunction | Pão e manteiga. | |
| Special Labels | aux:pass | Passive auxiliary | Foi foi roubado. |
| punct | Punctuation | Olá! | |
| dep | Unspecified dependency | (Usado para links desconhecidos) | |
| ROOT | Root of the sentence | Eu almoce. |
| Attachment | Full Name | Explanation | Example |
|---|---|---|---|
| :pass | Passive | Indicates a relationship in a passive voice construction. | nsubj:pass (A janela estava quebrada) |
| :nn | Noun Compound | Indicates that a noun is modifying another noun in a compound structure. | composto:nn (carregador de telefone) |
| :prep | Prepositional | Refines a modifier governed specifically by a preposition. | nmod:prep (O gato no tapete) |
| :assmod | Associative Modifier | Common in Romanian/Baltic languages; shows nouns modifying other nouns. | nmod:assmod (O carro do meu pai) |
| :poss | Possessive | Indicates ownership or a possessive relationship. | nmod:poss (Meu cachorro, chapéu do John) |
| :relcl | Relative Clause | Identifies a clause that modifies a noun phrase. | acl:relcl (O livro que li) |
| :tmod | Temporal Modifier | A modifier specifically describing time or duration. | nmod:tmod (Vou embora terça-feira) |
| :prt | Particle | Used for phrasal verb particles. | composto:prt (Desistir , encerrar desligar) |
| :rcomp | Relative Complement | Used for complements of relative clauses (common in Dutch). | advcl:rcomp (O homem que saiu) |
| :flat | Flat Modifier | Used for multi-word expressions that don't have a clear internal head. | flat:nome (Presidente 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, Califórnia |
| 🏔️ LOC | Non-political location (mountains, rivers) | Oceano Pacífico, Monte Everest, Alpes |
| 🏢 FAC | Facility (buildings, airports, highways) | Ponte Golden Gate, Aeroporto JFK, Burj Khalifa |
| 👤 PERSON | People (real or fictional) | Elon Musk, Harry Potter, Alan Turing |
| 🚩 NORP | Nationalities, religious or political groups | Americanos, Budistas, Democratas, Japoneses |
| 🏢 ORG | Organizations (companies, institutions) | Google, Nações Unidas, Apple, FIFA |
| 📅 DATE | Absolute or relative dates | 4 de julho de 2026, ontem, semana que vem |
| ⌚ TIME | Times smaller than a day | 9h30, pôr do sol, dez minutos |
| 🎊 EVENT | Named events (wars, festivals) | Segunda Guerra Mundial, Coachella, Jogos Olímpicos |
| 💰 MONEY | Monetary values, including unit | US$ 100, 5 milhões de euros, £ 50 |
| ‱ PERCENT | Percentage, including "%" | 20%, oitenta por cento, 0,5% |
| ⚖️ QUANTITY | Measurements (weight, distance) | 5 km, 100 libras, 30 metros quadrados |
| 🔢 ORDINAL | "First", "second", etc. | primeiro, 2º, nono |
| 🔢 CARDINAL | Numbers not classified elsewhere | 10, mil, três |
| 📦 PRODUCT | Objects, vehicles, foods, etc. (not services) | iPhone, Tesla Model S, Coca-Cola |
| 🎨 WORK_OF_ART | Titles of books, songs, etc. | Mona Lisa, Rapsódia Boêmia, Hamlet |
| 📜 LAW | Named legal documents | A Constituição, Tratado de Versalhes |
| 🗣️ LANGUAGE | Named languages | Inglês, Python, Mandarim |
Se processarmos a frase “O Google tem sede na Califórnia”, as camadas ficarão assim:
Lema: "Google", "be", "base", "in", "California"
UPOS: "PROPN(Proper Noun)", "AUX(Auxiliary)", "VERB(Verb)", "ADP(Adposition)", "PROPN(Proper Noun)"
XPPOS: "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" é o nsubj (sujeito nominal) do verbo "baseado" que é Raiz (Raiz da frase).
NER: "Google" é uma 🏢 ORG (Organização), "Califórnia" é uma 🌍 GPE (Entidade Geopolítica).
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