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 Russian UPOS tagging now.
| Group | Tag | Meaning | Example |
|---|---|---|---|
| Open Class | ADJ | Adjective | большой, старый, зеленый, непонятный, первый |
| ADV | Adverb | очень, завтра, внизу, где, там | |
| INTJ | Interjection | псст, ой, браво, привет | |
| NOUN | Noun (common) | девушка, кот, дерево, воздух, красота | |
| PROPN | Proper Noun | Мэри, Джон, Лондон, НАТО, HBO | |
| VERB | Verb | беги, беги, беги, ешь, ел, ел | |
| Closed Class | ADP | Adposition | в, до, во время |
| AUX | Auxiliary | есть, сделал (сделал), будет (сделать), должен (сделать) | |
| CONJ | Conjunction | и, или, но (устаревший тег) | |
| CCONJ | Coordinating Conjunction | и, или, но | |
| SCONJ | Subordinating Conjunction | если, пока, что | |
| DET | Determiner | а, ан, | |
| NUM | Numeral | 1 января 2017 года, семьдесят семь, MMXIV | |
| PART | Particle | , а не | |
| PRON | Pronoun | Я, ты, он, она, я, себя, кто-то | |
| 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 Russian 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 | Илон ест. |
| csubj | Clausal subject | То, что он сделал, было неправильно. | |
| obj | Direct object | Я вижу луну. | |
| iobj | Indirect object | Она сделала мне подарок. | |
| ccomp | Clausal complement (finite) | Он сказал, что устал. | |
| xcomp | Open clausal complement | Я хочу пойти. | |
| Non-Core Dependents | obl | Oblique nominal | Он сел на стул. |
| vocative | Vocative | Джон, иди сюда! | |
| expl | Expletive | Там есть кот. | |
| dislocated | Dislocated element | Этот человек, я его знаю. | |
| advcl | Adverbial clause modifier | Я ушел после его прибытия. | |
| advmod | Adverbial modifier | Беги быстро. | |
| discourse | Discourse element | Ну, я не уверен. | |
| aux | Auxiliary | Я могу видеть. | |
| cop | Copula | Она счастлива. | |
| mark | Subordinating marker | Я знаю, что вы знаете. | |
| Nominal Dependents | nmod | Nominal modifier | Дверь автомобиля. |
| appos | Appositional modifier | Сэм, мой друг. | |
| nummod | Numeric modifier | Семь дней. | |
| acl | Adjectival clause | План на победу. | |
| amod | Adjectival modifier | голубое небо. | |
| det | Determiner | Конец. | |
| case | Case marking | Король Франции. | |
| fixed | Fixed multiword expression | Несмотря на это. | |
| flat | Flat multiword name | Нью-Йорк Город. | |
| compound | Compound noun | Телефонная будка. | |
| list | List element | Телефон, ключи, кошелек. | |
| Coordination | conj | Conjunct | Хлеб и масло. |
| cc | Coordinating conjunction | Хлеб и масло. | |
| Special Labels | aux:pass | Passive auxiliary | Оно было украдено. |
| punct | Punctuation | Привет! | |
| dep | Unspecified dependency | (Используется для неизвестных ссылок) | |
| ROOT | Root of the sentence | Я съел обед. |
| Attachment | Full Name | Explanation | Example |
|---|---|---|---|
| :pass | Passive | Indicates a relationship in a passive voice construction. | nsubj:pass (окно было разбито) |
| :nn | Noun Compound | Indicates that a noun is modifying another noun in a compound structure. | соединение:nn (зарядное устройство телефона) |
| :prep | Prepositional | Refines a modifier governed specifically by a preposition. | nmod:prep (Кошка на коврике) |
| :assmod | Associative Modifier | Common in Romanian/Baltic languages; shows nouns modifying other nouns. | nmod:assmod (Машина моего отца) |
| :poss | Possessive | Indicates ownership or a possessive relationship. | nmod:poss (Моя собака, Шляпа Джона) |
| :relcl | Relative Clause | Identifies a clause that modifies a noun phrase. | acl:relcl (Книга, которую я прочитал) |
| :tmod | Temporal Modifier | A modifier specifically describing time or duration. | nmod:tmod (я уезжаю вторник) |
| :prt | Particle | Used for phrasal verb particles. | compound:prt (отключить включить, выключить выключить) |
| :rcomp | Relative Complement | Used for complements of relative clauses (common in Dutch). | advcl:rcomp (Человек, который ушел) |
| :flat | Flat Modifier | Used for multi-word expressions that don't have a clear internal head. | квартира:имя (Президент Обама) |
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) | США, Нью-Йорк, Франция, Калифорния |
| 🏔️ LOC | Non-political location (mountains, rivers) | Тихий океан, Эверест, Альпы |
| 🏢 FAC | Facility (buildings, airports, highways) | Мост Золотые Ворота, аэропорт имени Джона Кеннеди, Бурдж-Халифа |
| 👤 PERSON | People (real or fictional) | Илон Маск, Гарри Поттер, Алан Тьюринг |
| 🚩 NORP | Nationalities, religious or political groups | Американцы, буддисты, демократы, японцы |
| 🏢 ORG | Organizations (companies, institutions) | Google, ООН, Apple, FIFA |
| 📅 DATE | Absolute or relative dates | 4 июля 2026 г., вчера, на следующей неделе |
| ⌚ TIME | Times smaller than a day | 9:30 утра, закат, десять минут |
| 🎊 EVENT | Named events (wars, festivals) | Вторая мировая война, Коачелла, Олимпийские игры |
| 💰 MONEY | Monetary values, including unit | 100 долларов США, 5 миллионов евро, 50 фунтов стерлингов |
| ‱ PERCENT | Percentage, including "%" | 20%, восемьдесят процентов, 0,5% |
| ⚖️ QUANTITY | Measurements (weight, distance) | 5 км, 100 фунтов, 30 квадратных метров |
| 🔢 ORDINAL | "First", "second", etc. | первый, 2-й, девятый |
| 🔢 CARDINAL | Numbers not classified elsewhere | 10, тысяча, три |
| 📦 PRODUCT | Objects, vehicles, foods, etc. (not services) | iPhone, Tesla Model S, Coca-Cola |
| 🎨 WORK_OF_ART | Titles of books, songs, etc. | Мона Лиза, Богемская рапсодия, Гамлет |
| 📜 LAW | Named legal documents | Конституция, Версальский договор |
| 🗣️ LANGUAGE | Named languages | Английский, Python, Мандарин |
Если мы обработаем фразу «Google базируется в Калифорнии», слои будут выглядеть так:
Лемма: "Google", "be", "base", "in", "California"
УПОС: "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" — это nsubj (именное подлежащее) глагола "based", который является Root (коренем предложения).
NER: «Google» — это 🏢 ORG (организация), «Калифорния» — это 🌍 GPE (геополитическая организация).
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