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 Hindi UPOS tagging now.
| Group | Tag | Meaning | Example |
|---|---|---|---|
| Open Class | ADJ | Adjective | बड़ा, पुराना, हरा, समझ से बाहर, पहला |
| ADV | Adverb | बहुत, कल, नीचे, कहाँ, वहाँ | |
| INTJ | Interjection | श्श्, आह, शाबाश, नमस्ते | |
| NOUN | Noun (common) | लड़की, बिल्ली, पेड़, हवा, सुंदरता | |
| PROPN | Proper Noun | मैरी, जॉन, लंदन, नाटो, एचबीओ | |
| VERB | Verb | दौड़ना, दौड़ता है, दौड़ते हुए, खाना, खाया, खाया हुआ | |
| Closed Class | ADP | Adposition | में, को, के दौरान |
| AUX | Auxiliary | है, कर चुका है, करेगा, करना चाहिए | |
| CONJ | Conjunction | और, या, लेकिन (विरासत टैग) | |
| CCONJ | Coordinating Conjunction | और, या, लेकिन | |
| SCONJ | Subordinating Conjunction | यदि, जबकि, कि | |
| DET | Determiner | एक, —, — | |
| NUM | Numeral | 1, 2017, एक, सतहत्तर, MMXIV | |
| PART | Particle | का/की/के, नहीं | |
| PRON | Pronoun | मैं, आप, वह, वह, मैं खुद, वे खुद, कोई | |
| 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.
The Hindi XPOS tags follow the BIS (Bureau of Indian Standards) or IIIT-Hyderabad tagset. This system is designed to handle Hindi's SOV (Subject-Object-Verb) structure and its use of postpositions (grammatical markers that follow the noun).
One key distinction in this set is the separation of Main Verbs (VM) from Auxiliary Verbs (VAUX) and the specific tagging of Proper Noun Compounds (NNPC), which is crucial for accurate Named Entity Recognition.
The system emphasizes the distinction between main and auxiliary verbs and highlights the vital role of postpositions (PSP) which govern case relationships in Indo-Aryan languages.
Try our Hindi XPOS tagging now.
| Category | Tag | Meaning | Example |
|---|---|---|---|
| Nouns | NN | Common Noun | किताब (book), शहर (city) |
| NNP | Proper Noun | दिल्ली (Delhi), भारत (India) | |
| NNPC | Proper Noun Compound (Part of name) | महात्मा गांधी (The 'Mahatma' part) | |
| Pronouns | PRP | Personal Pronoun | मैं (I), हम (we), आप (you) |
| DEM | Demonstrative Pronoun | यह (this), वह (that) | |
| Verbs | VM | Main Verb | खा (eat), चल (walk), देख (see) |
| VAUX | Auxiliary Verb | है (is), था (was), रहा (continuing) | |
| Adjectives | JJ | Adjective | बड़ा (big), नीला (blue), अच्छा (good) |
| Adverbs | RB | Adverb | तेज़ (fast), धीरे (slowly), अक्सर (often) |
| Postposition | PSP | Postposition (Case Marker) | ने (ergative), को (to), में (in), से (from) |
| Quantifiers | QC | Cardinal Numeral | एक (one), दो (two), दस (ten) |
| QO | Ordinal Numeral | पहला (first), दूसरा (second) | |
| QF | General Quantifier | बहुत (much), कम (less), थोड़ा (little) | |
| Particles | RP | Particle (Emphasis) | भी (also), ही (only), तो (so) |
| NEG | Negative Particle | नहीं (not), न (no), मत (do not) | |
| Others | CC | Conjunction | और (and), या (or), लेकिन (but) |
| WQ | Wh-word (Interrogative) | क्या (what), क्यों (why), कहाँ (where) | |
| NST | Noun Spatio-Temporal (Locative) | ऊपर (above), नीचे (below), पास (near) | |
| SYM | Symbol / Punctuation | ।, ,, ?, ! | |
| INJ | Interjection | अरे (hey), वाह (wow) |
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 | एलोन खाता है। |
| csubj | Clausal subject | उसने जो किया वह गलत था। | |
| obj | Direct object | मैं चाँद देखता हूँ। | |
| iobj | Indirect object | उसने मुझे एक उपहार दिया। | |
| ccomp | Clausal complement (finite) | उसने कहा कि वह थका हुआ था। | |
| xcomp | Open clausal complement | मैं जाना चाहता हूँ। | |
| Non-Core Dependents | obl | Oblique nominal | वह कुर्सी पर बैठा। |
| vocative | Vocative | जॉन, यहाँ आओ! | |
| expl | Expletive | वहाँ एक बिल्ली है। | |
| dislocated | Dislocated element | उस आदमी को मैं जानता हूँ। | |
| advcl | Adverbial clause modifier | उसके आने के बाद मैं चला गया। | |
| advmod | Adverbial modifier | तेज़ दौड़ो। | |
| discourse | Discourse element | खैर, मुझे यकीन नहीं है। | |
| aux | Auxiliary | मैं देख सकता हूँ। | |
| cop | Copula | वह खुश है। | |
| mark | Subordinating marker | मुझे पता है कि तुम जानते हो। | |
| Nominal Dependents | nmod | Nominal modifier | गाड़ी का दरवाज़ा। |
| appos | Appositional modifier | सैम, मेरा दोस्त। | |
| nummod | Numeric modifier | सात दिन। | |
| acl | Adjectival clause | जीतने की योजना। | |
| amod | Adjectival modifier | नीला आसमान। | |
| det | Determiner | अंत। | |
| case | Case marking | फ्रांस का राजा। | |
| fixed | Fixed multiword expression | इसके बावजूद। | |
| flat | Flat multiword name | न्यूयॉर्क शहर। | |
| compound | Compound noun | फ़ोन बूथ। | |
| list | List element | फ़ोन, चाबियाँ, बटुआ। | |
| Coordination | conj | Conjunct | रोटी और मक्खन। |
| cc | Coordinating conjunction | रोटी और मक्खन। | |
| Special Labels | aux:pass | Passive auxiliary | यह चोरी हो गया। |
| punct | Punctuation | नमस्ते! | |
| dep | Unspecified dependency | (अज्ञान संबंधों के लिए उपयोग किया जाता है) | |
| ROOT | Root of the sentence | मैंने दोपहर का भोजन किया। |
| Attachment | Full Name | Explanation | Example |
|---|---|---|---|
| :pass | Passive | Indicates a relationship in a passive voice construction. | nsubj:pass (खिड़की टूट गई थी) |
| :nn | Noun Compound | Indicates that a noun is modifying another noun in a compound structure. | compound:nn (फ़ोन चार्जर) |
| :prep | Prepositional | Refines a modifier governed specifically by a preposition. | nmod:prep (चटाई पर बिल्ली) |
| :assmod | Associative Modifier | Common in Romanian/Baltic languages; shows nouns modifying other nouns. | nmod:assmod (मेरे पिता की गाड़ी) |
| :poss | Possessive | Indicates ownership or a possessive relationship. | nmod:poss (मेरा कुत्ता, जॉन की टोपी) |
| :relcl | Relative Clause | Identifies a clause that modifies a noun phrase. | acl:relcl (वह पुस्तक जो मैंने पढ़ी) |
| :tmod | Temporal Modifier | A modifier specifically describing time or duration. | nmod:tmod (मैं मंगलवार को जा रहा हूँ) |
| :prt | Particle | Used for phrasal verb particles. | compound:prt (हार मानना, बंद करना) |
| :rcomp | Relative Complement | Used for complements of relative clauses (common in Dutch). | advcl:rcomp (वह आदमी जो चला गया) |
| :flat | Flat Modifier | Used for multi-word expressions that don't have a clear internal head. | flat:name (राष्ट्रपति ओबामा) |
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) | भारत, नई दिल्ली, फ्रांस, कैलिफ़ोर्निया |
| 🏔️ LOC | Non-political location (mountains, rivers) | प्रशांत महासागर, माउंट एवरेस्ट, आल्प्स पर्वत |
| 🏢 FAC | Facility (buildings, airports, highways) | गोल्डन गेट ब्रिज, जेएफके हवाई अड्डा, बुर्ज खलीफा |
| 👤 PERSON | People (real or fictional) | एलोन मस्क, हैरी पॉटर, एलन ट्यूरिंग |
| 🚩 NORP | Nationalities, religious or political groups | भारतीय, बौद्ध, डेमोक्रेट्स, जापानी |
| 🏢 ORG | Organizations (companies, institutions) | गूगल, संयुक्त राष्ट्र, एप्पल, फीफा |
| 📅 DATE | Absolute or relative dates | 4 जुलाई, 2026, कल, अगले सप्ताह |
| ⌚ TIME | Times smaller than a day | सुबह 9:30 बजे, सूर्यास्त, दस मिनट |
| 🎊 EVENT | Named events (wars, festivals) | द्वितीय विश्व युद्ध, कोचेला, ओलंपिक खेल |
| 💰 MONEY | Monetary values, including unit | $100, 5 मिलियन यूरो, £50 |
| ‱ PERCENT | Percentage, including "%" | 20%, अस्सी प्रतिशत, 0.5% |
| ⚖️ QUANTITY | Measurements (weight, distance) | 5 किमी, 50 किलोग्राम, 30 वर्ग मीटर |
| 🔢 ORDINAL | "First", "second", etc. | पहला, दूसरा, नौवां |
| 🔢 CARDINAL | Numbers not classified elsewhere | 10, एक हजार, तीन |
| 📦 PRODUCT | Objects, vehicles, foods, etc. (not services) | आईफोन, टेस्ला मॉडल एस, कोका-कोला |
| 🎨 WORK_OF_ART | Titles of books, songs, etc. | मोना लिसा, बोहेमियन रैप्सोडी, हैमलेट |
| 📜 LAW | Named legal documents | संविधान, वर्साय की संधि |
| 🗣️ LANGUAGE | Named languages | हिंदी, पायथन, मंदारिन |
यदि हम वाक्य "गूगल कैलिफ़ोर्निया में स्थित है" (Google is based in California) को संसाधित करते हैं, तो विश्लेषण की परतें इस प्रकार दिखती हैं:
मूल शब्द (Lemma): "गूगल", "कैलिफ़ोर्निया", "में", "स्थित", "होना"
UPOS: "PROPN(व्यक्तिवाचक संज्ञा)", "PROPN(व्यक्तिवाचक संज्ञा)", "ADP(परसर्ग/संबोधक)", "ADJ(विशेषण)", "AUX(सहायक क्रिया)"
XPOS (BIS/IIIT): "NNP", "NNP", "PSP", "JJ", "VAUX"
DEP: "गूगल" संज्ञा कर्ता (nsubj) है, "स्थित" मुख्य शब्द (Root) है। "कैलिफ़ोर्निया" परसर्ग "में" के साथ क्रिया-विशेषण रूप (obl) से जुड़ा है। "है" सहायक क्रिया (aux) है।
NER: "गूगल" एक 🏢 ORG (संगठन) है, "कैलिफ़ोर्निया" एक 🌍 GPE (भू-राजनीतिक इकाई) है।
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