Universal POS, Detailed POS, NER, DEP

UPOS (Universal POS)

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 Greek UPOS tagging now.

UPOS Universal Part-of-Speech
Group Tag Meaning Example
Open Class ADJ Adjective μεγάλος, παλιός, πράσινος, ακατανόητος, πρώτος
ADV Adverb πολύ, αύριο, κάτω, πού, εκεί
INTJ Interjection ψιτ, ωχ, μπράβο, γεια
NOUN Noun (common) κορίτσι, γάτα, δέντρο, αέρας, ομορφιά
PROPN Proper Noun Μαρία, Ιωάννης, Λονδίνο, ΝΑΤΟ, HBO
VERB Verb τρέχω, τρέχει, τρέξιμο, τρώω, έφαγα, φαγωμένος
Closed Class ADP Adposition σε, προς, κατά τη διάρκεια
AUX Auxiliary είναι, έχει (κάνει), θα (κάνει), πρέπει (να κάνει)
CONJ Conjunction και, ή, αλλά (παλιά ετικέτα)
CCONJ Coordinating Conjunction και, ή, αλλά
SCONJ Subordinating Conjunction αν, ενώ, ότι
DET Determiner ένας, μια, το
NUM Numeral 1, 2017, ένα, εβδομήντα επτά, MMXIV
PART Particle της/του (γενική), δεν
PRON Pronoun εγώ, εσύ, αυτός, αυτή, ο εαυτός μου, οι ίδιοι, κάποιος
Other PUNCT Punctuation ., (, ), ?, ]
SYM Symbol $, %, +, −, :), 🐻
X Other / Foreign sfpksdpsxmsa, ..., foreign words
SPACE Space newlines, tabs, extra spaces

XPOS (Detailed POS)

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 Greek XPOS tagging now.

General xpos Morphological Details
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)

Dependency

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.

DEP Full Syntactic Dependency Labels
Category Label Meaning Example (Token in bold)
Core Arguments nsubj Nominal subject Ο Elon τρώει.
csubj Clausal subject Αυτό που έκανε ήταν λάθος.
obj Direct object Βλέπω το φεγγάρι.
iobj Indirect object Μου έδωσε ένα δώρο.
ccomp Clausal complement (finite) Είπε ότι ήταν κουρασμένος.
xcomp Open clausal complement Θέλω να πάω.
Non-Core Dependents obl Oblique nominal Κάθισε στην καρέκλα.
vocative Vocative Γιάννη, έλα εδώ!
expl Expletive Υπάρχει μια γάτα εκεί.
dislocated Dislocated element Εκείνον τον άντρα, τον ξέρω.
advcl Adverbial clause modifier Έφυγα αφότου έφτασε.
advmod Adverbial modifier Τρέξε γρήγορα.
discourse Discourse element Λοιπόν, δεν είμαι σίγουρος.
aux Auxiliary Μπορώ να δω.
cop Copula Αυτή είναι χαρούμενη.
mark Subordinating marker Ξέρω ότι ξέρεις.
Nominal Dependents nmod Nominal modifier Η πόρτα του αυτοκινήτου.
appos Appositional modifier Σαμ, ο φίλος μου.
nummod Numeric modifier Επτά ημέρες.
acl Adjectival clause Το σχέδιο για νίκη.
amod Adjectival modifier Ο γαλάζιος ουρανός.
det Determiner Το τέλος.
case Case marking Ο βασιλιάς της Γαλλίας.
fixed Fixed multiword expression Παρά από αυτό.
flat Flat multiword name Πόλη της Αθήνας.
compound Compound noun Τηλεφωνικός θάλαμος.
list List element Τηλέφωνο, κλειδιά, πορτοφόλι.
Coordination conj Conjunct Ψωμί και βούτυρο.
cc Coordinating conjunction Ψωμί και βούτυρο.
Special Labels aux:pass Passive auxiliary Κλάπηκε.
punct Punctuation Γεια σας!
dep Unspecified dependency (Χρησιμοποιείται για άγνωστους συνδέσμους)
ROOT Root of the sentence Έφαγα μεσημεριανό.

Common Dependency Attachments (Sub-labels)
Attachment Full Name Explanation Example
:pass Passive Indicates a relationship in a passive voice construction. nsubj:pass (Το παράθυρο έσπασε)
:nn Noun Compound Indicates that a noun is modifying another noun in a compound structure. compound:nn (Φορτιστής τηλεφώνου)
:prep Prepositional Refines a modifier governed specifically by a preposition. nmod:prep (Η γάτα πάνω στο χαλάκι)
:assmod Associative Modifier Common in Romanian/Baltic languages; shows nouns modifying other nouns. nmod:assmod (Το αυτοκίνητο του πατέρα μου)
:poss Possessive Indicates ownership or a possessive relationship. nmod:poss (Ο σκύλος μου, το καπέλο του Γιάννη)
:relcl Relative Clause Identifies a clause that modifies a noun phrase. acl:relcl (Το βιβλίο που διάβασα)
:tmod Temporal Modifier A modifier specifically describing time or duration. nmod:tmod (Φεύγω την Τρίτη)
:prt Particle Used for phrasal verb particles. compound:prt (Παρατούμαι, κλείνω)
:rcomp Relative Complement Used for complements of relative clauses (common in Dutch). advcl:rcomp (Ο άντρας που έφυγε)
:flat Flat Modifier Used for multi-word expressions that don't have a clear internal head. flat:nameΠρόεδρος Ομπάμα)

Named Entity Recognition

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.

NER Named Entity Recognition
Label Meaning Example
🌍 GPE Geopolitical entity (countries, cities, states) Ελλάδα, Αθήνα, Γαλλία, Καλιφόρνια
🏔️ LOC Non-political location (mountains, rivers) Ειρηνικός Ωκεανός, Έβερεστ, Άλπεις
🏢 FAC Facility (buildings, airports, highways) Παρθενώνας, Αεροδρόμιο Ελευθέριος Βενιζέλος, Burj Khalifa
👤 PERSON People (real or fictional) Κωνσταντίνος Καραθεοδωρή, Χάρι Πότερ, Οδυσσέας Ελύτης
🚩 NORP Nationalities, religious or political groups Έλληνας, Βουδιστής, Δημοκρατικοί, Ιάπωνας
🏢 ORG Organizations (companies, institutions) Google, Ηνωμένα Έθνη, Apple, FIFA
📅 DATE Absolute or relative dates 4 Ιουλίου, 2026, χθες, την επόμενη εβδομάδα
⌚ TIME Times smaller than a day 9:30 π.μ., ηλιοβασίλεμα, δέκα λεπτά
🎊 EVENT Named events (wars, festivals) Δεύτερος Παγκόσμιος Πόλεμος, Φεστιβάλ Αθηνών, Ολυμπιακοί Αγώνες
💰 MONEY Monetary values, including unit 100 $, 5 εκατομμύρια ευρώ, £50
‱ PERCENT Percentage, including "%" 20%, ογδόντα τοις εκατό, 0,5%
⚖️ QUANTITY Measurements (weight, distance) 5 χλμ, 50 κιλά, 30 τετραγωνικά μέτρα
🔢 ORDINAL "First", "second", etc. πρώτος, 2ος, ένατος
🔢 CARDINAL Numbers not classified elsewhere 10, χίλια, τρία
📦 PRODUCT Objects, vehicles, foods, etc. (not services) iPhone, Tesla Model S, Coca-Cola
🎨 WORK_OF_ART Titles of books, songs, etc. Μόνα Λίζα, Bohemian Rhapsody, Άμλετ
📜 LAW Named legal documents Το Σύνταγμα της Ελλάδας, Συνθήκη των Βερσαλλιών
🗣️ LANGUAGE Named languages Ελληνικά, Python, Μανδαρινικά

Παράδειγμα επεξεργασίας φυσικής γλώσσας (NLP Example)

Αν αναλύσουμε την πρόταση „Η Google έχει την έδρα της στην Αθήνα“ (Google has its headquarters in Athens), τα διάφορα επίπεδα ανάλυσης φαίνονται παρακάτω:

Lemma (Λήμμα): "Google", "έχω", "έδρα", "ο", "Αθήνα"
UPOS (Καθολικά μέρη του λόγου): "PROPN(Κύριο όνομα)", "VERB(Ρήμα)", "NOUN(Ουσιαστικό)", "ADP(Πρόθεση)", "PROPN(Κύριο όνομα)"
XPOS (Λεπτομερή μορφολογικά χαρακτηριστικά): "N(Prop,Nom)", "V(Act,Ind,Pres)", "N(Subst,Acc)", "Prep", "N(Prop,Acc)"
DEP (Συντακτικές εξαρτήσεις): „Google“ είναι το nsubj (υποκείμενο) του ρήματος „έχει“ που είναι το Root (ρίζα της πρότασης). „έδρα“ είναι το obj (αντικείμενο). „Αθήνα“ είναι το obl (επιρρηματικός προσδιορισμός) συνδεδεμένο μέσω της πρόθεσης „στην“.
NER (Αναγνώριση ονοματισμένων οντοτήτων): „Google“ είναι 🏢 ORG (Οργανισμός), και „Αθήνα“ είναι 🌍 GPE (Γεωπολιτική οντότητα).

Part-of-Speech for Main Languages

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