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An adjective is a part of speech characteristically used to express properties and modify nouns. It can also occur in predicative constructions, as in The cube is red. Its classification depends on its grammatical behavior, beyond whether its meaning sounds descriptive.^[ref]

In an original simple formal semantics, let red objects form $R=\{1,2\}$ and cubes form $C=\{2,3\}$. The expression red cube can denote the intersection $R\cap C=\{2\}$. This illustrates how an adjective can contribute a property to a noun phrase, while leaving the grammatical classification distinct from that particular semantic rule.

Modification alone is insufficient evidence for adjective status. In the Universal Dependencies scheme, a noun used to modify another noun in a compound remains tagged as a noun. Clear category criteria make linguistic annotation reproducible instead of treating every modifier as the same class.

A common noun is a noun used to classify an entity or concept rather than to provide an individual name. It can describe a concrete thing, an event or an abstraction. The contrast with a proper noun concerns grammatical use, beyond whether the referent happens to be unique in a particular conversation.^[ref]

In the village teacher, teacher remains a common noun even if the village has only one teacher. In two explosions, explosions names events and shows plural grammatical number; an event meaning does not make the form a verb. These examples separate semantic reference from lexical category.

For a text corpus using Universal Dependencies, the tag NOUN identifies this category while PROPN identifies proper nouns. Sentence-initial capitalization is therefore inadequate as the sole labeling rule. A repeatable annotation procedure considers context and the scheme's category definitions.

CoNLL-U is a plain-text format for exchanging Universal Dependencies linguistic annotation. A word line has ten tab-separated fields: identifier, form, lemma, universal and optional local part of speech, features, basic head, basic relation, enhanced dependencies and miscellaneous information. Blank lines separate sentences; hash-prefixed comments can describe each sentence.^[ref]

An original two-word example, with literal tab separators, is:The first word depends on word two as its subject; word two is attached to the notional root numbered zero. Underscores indicate unspecified values. A saved sentence ends with its blank separator, including at the end of a file.

The specification also requires UTF-8 text with NFC Unicode normalization and LF line endings. Range identifiers represent multiword tokens and decimal identifiers represent empty nodes under additional rules. Consequently, counting ten columns is useful but insufficient for validating every CoNLL-U record.

A determiner is a grammatical category whose members help specify the reference of a noun phrase in context. They can signal distinctions such as definite versus indefinite reference, proximity or quantity. Their contribution differs from the descriptive property supplied by a typical adjective.^[ref]

Compare a red box, the red box and this red box. The descriptive words can remain fixed while the expressions impose different expectations about identifying the referent. In a display with several red boxes, pointing can help interpret this, while an earlier mention can help establish the intended referent of the.

Classification also requires a stated scheme. Universal Dependencies includes articles such as a and the under DET, but uses a separate numerical label for cardinal numbers. A familiar broad description like “a word before a noun” is therefore too weak to reproduce the intended linguistic annotation.

A lemma is a conventional citation form used to represent a lexical entry or a set of related grammatical forms. It differs from a lexeme, the abstract vocabulary item being represented, and from an arbitrary truncation of a word's spelling. The convention is language-specific.^[ref]

In a simple English analysis, walks, walked and walking can be assigned the lemma walk. The Universal Dependencies guidelines also distinguish inflection from derivational morphology: organizations has citation form organization, not organize or organ.

Context can be needed before the citation form is chosen. The spelling saw can name a tool or occur as a past form of see; a process that uses spelling alone cannot settle every such ambiguity. Recording the part of speech, intended word sense and the original occurrence makes a text corpus analysis more reproducible than retaining only the normalized label.

Linguistic annotation adds explicit analytical information to language data, such as word boundaries, part of speech, grammatical number or syntactic dependencies. The original text and the assigned labels are distinct: an annotation records an analysis under stated conventions, rather than being an uninterpreted observation.

In the sentence Birds fly, one analysis assigns the lemma forms bird and fly, the categories noun and verb, and a subject relationship connecting the first word to the second. Universal Dependencies represents such information in CoNLL-U, separating word forms, lemma forms, grammatical features and dependency fields.^[ref]

Keeping those layers separate permits a revised grammatical analysis without silently changing the underlying recording. It also makes disagreement inspectable: two annotators may agree on the text but assign different categories. A reusable annotated text corpus therefore needs its conventions and ambiguous cases documented alongside the labels.

A noun is a part of speech whose members commonly name entities or concepts and head noun phrases. Meanings alone do not supply a complete classification: a noun can name an event or property as readily as a physical object. Distribution and inflection provide additional grammatical evidence.^[ref]

For example, explosion names an event, but behaves as a noun in the explosion and two explosions. Its connection with an event does not make it a verb; compare The shell exploded. Likewise, redness is a noun even though it names a property associated with the adjective red.

In Universal Dependencies, the tag NOUN is reserved for common nouns, with PROPN used for proper nouns. That distinction matters when reproducing an analysis: a count of every traditionally named noun is not necessarily a count of only tokens tagged NOUN.

An object is a grammatical relation assigned to certain complements of a verb. In a typical active construction it identifies a core participant other than the subject, often an entity affected by the event. This is a grammatical classification rather than a requirement that the referent be a physical object.^[ref]

In Mira opened the gate, the gate is an object. In The gate was opened by Mira, the same participant is instead the subject of a passive voice construction. The event can remain closely related while the grammatical relationships change.

An explicit annotation scheme also needs boundaries among complements. Universal Dependencies distinguishes obj from iobj and from other dependent relations; a traditional label “object” does not automatically determine the appropriate code. This makes syntactic dependency criteria part of the analysis needed to compare annotated text corpus resources.

A part of speech is a grammatical word category identified by patterns of distribution, combination and, where relevant, inflection. Categories such as noun, verb and adjective help describe what an expression can do in a construction. Meaning is evidence, but a rule equating a category with one broad kind of meaning is insufficient.

For example, record is a noun in the record and a verb in record the result. The same spelling can therefore require different labels when its context changes. A computational annotation scheme must state whether it assigns categories to lexical entries, individual occurrences or both.^[ref]

Universal Dependencies separates a broad part of speech label from additional grammatical features. Two forms can share the label NOUN while differing in grammatical number. Keeping category and features distinct makes an analysis of a text corpus reproducible without multiplying category labels for every possible form.

Passive voice is a grammatical construction that changes how an event's participants are expressed, typically placing an affected participant in the subject relation while omitting the actor or expressing it differently. It belongs to grammatical voice, not simply to a choice of slow or indirect wording.^[ref]

Compare The mechanic repaired the pump with The pump was repaired by the mechanic. Both can describe the same repair, but the pump changes from object to subject; the mechanic is expressed in a separate phrase. Omitting that phrase gives The pump was repaired without specifying who performed the repair.

This is useful for separating thematic roles from grammatical relationships. A representation that treats every subject as the actor will misdescribe the passive example. The Universal Dependencies label nsubj:pass preserves subject status while recording the passive construction, making the analysis inspectable in a text corpus.

A pronoun is a member of a grammatical category whose uses commonly occupy nominal positions while their interpretation is recovered from context. A previous noun phrase can supply that context, but is not required: I can identify the current speaker without repeating an earlier name.^[ref]

Consider The robot moved beside the box. It stopped. Under a stipulated reading where both objects are possible referents, the spelling it alone does not select one. Grammatical number and syntax can constrain the possibilities while leaving a contextual decision unresolved. The category of the expression and the identity of its referent are distinct annotation questions.

The border with determiners also depends on the adopted scheme. Universal Dependencies documents PRON and DET using characteristic distribution and language-specific conventions. An explicit inventory helps compare text corpus annotations without assuming that a familiar label always covers exactly the same words in every language.

A proper noun is a noun used as a name, or as a nominal part of a name, for a specific individual, place or entity. Its naming function differs from the classifying use of a common noun. Capitalization can be a writing convention associated with that distinction, but is not by itself a universal grammatical test.^[ref]

In the original example Dara is a teacher, Dara functions as a name while teacher classifies the person. By contrast, Teacher arrived late can capitalize a common noun merely because it begins the written sentence. A classifier using only the initial capital would confuse these roles.

The Universal Dependencies code PROPN also does not automatically apply to every component of an arbitrarily long name. The scheme retains the appropriate categories for many component words in phrase-like names. Explicit criteria therefore matter when counting names or evaluating linguistic annotation.

A subject is a grammatical relation identified through language-specific structural tests, such as word order and grammatical agreement. It often corresponds to the actor in a simple active clause, but that semantic association is not its definition. A noun phrase can be a subject without describing an intentional action.^[ref]

Compare A gust broke the branch and The branch was broken by a gust. The first has a gust as its subject; in the passive voice version, the branch has that relation. The participants' involvement in the event has not simply exchanged places. Separating grammatical relations from thematic roles explains the contrast.

In Universal Dependencies, a nominal passive subject can receive nsubj:pass, explicitly preserving its subject status. Such a representation supports a testable structural account and prevents a procedure from assigning “subject” solely to whichever expression appears to name a doer.

A syntactic dependency is a typed relation between an expression and its syntactic head under an explicit grammatical representation. In basic Universal Dependencies, the words form a rooted tree: one word attaches to a notional ROOT, and each other word has one basic head. An enhanced representation can instead form a more general graph.^[ref]

For the original example The small birds fly, number the words one through four. In head-to-dependent notation, the links are 4→3 for the subject, 3→1 for the determiner, and 3→2 for the adjective; 0→4 identifies the sentence head. The determiner link spans a nonadjacent word, showing why dependency is not merely adjacency.

The direction of an arrow and the meaning of each relation must be stated. The project also notes that some dependency labels encode relationships without asserting a simple head-subordinate linguistic analysis. A mechanically valid tree therefore remains a representation to justify, rather than a proof of its own grammatical interpretation.

Universal Dependencies is a framework for comparable grammatical annotation across languages. It combines part of speech labels, morphological features and typed syntactic dependencies, while allowing documented language-specific choices. The framework supplies a common representation rather than a claim that all languages express every distinction identically.^[ref]

For Birds fly, a compatible analysis identifies Birds as a noun with plural grammatical number, gives it the lemma bird, and links it to fly with the subject relation nsubj. These are distinct annotation decisions: changing a lexical convention need not require changing the sentence's dependency structure.

Basic dependencies form a rooted tree, whereas an enhanced representation can contain additional relations and need not remain a tree.^[ref] Keeping the layers explicit helps compare parser output and manually analyzed text corpus resources. A valid interchange file and an empirically justified grammatical analysis remain different achievements.

A verb is a part of speech that commonly organizes a clause, specifying relationships among its participants and contributing an event or state description. Forms of a verb may express grammatical tense, grammatical aspect or grammatical agreement, though the mechanisms differ across languages.^[ref]

Compare Rin sleeps with Rin opens the box. The second construction contains an object in addition to its subject; knowing a verb includes knowing how it combines with other expressions. Calling verbs “action words” misses examples such as know, which describes a state.

An annotation scheme must also define its boundaries. Universal Dependencies assigns main verbs the label VERB while distinguishing auxiliary uses with AUX. Thus a traditional grammatical description and a particular computational tag inventory need not draw every boundary identically. Stating the scheme makes category counts in a text corpus interpretable.

Word segmentation identifies the units treated as words in a particular linguistic analysis. Written spaces provide one possible cue, but an orthographic unit need not correspond to one syntactic unit. The boundary convention must therefore be stated before counting words or assigning syntactic dependencies.^[ref]

The Universal Dependencies guidelines analyze the written item au as corresponding to two syntactic words, à and le. Extending that example to au village, an orthographic count gives two units, while the syntactic analysis gives three. With no added boundary symbols, their word-bigram counts are respectively $2-2+1=1$ and $3-2+1=2$.

This is a change in representation, not evidence that the utterance became longer. Word segmentation affects n-gram counts, lemma assignment and linguistic annotation. A reproducible text corpus records how boundaries were chosen and how original written forms map to the analyzed units.