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Research draft

noun

vr.tr.noun · INF.MED

Let an agent handle nouns by type, grammar, inflection and usage across languages, for writing, learning and language technology.

Thing Registry Information and virtual systems

Research draft, second pass

A second pass drafted this model: the structure a model of this thing needs, and what is known about it in the world. The line under this one says how the second half was obtained - researched against sources, or recalled without web access, in which case nothing here was read anywhere and every claim is a lead to verify. Unreviewed either way.

written by Claude from model knowledge without web access - no source was read, every claim is a lead to verify

Researched by: Claude

Purpose and description

Let an agent handle nouns by type, grammar, inflection and usage across languages, for writing, learning and language technology.

A word class that names people, places, things, ideas or qualities, typically functioning as the subject or object of a verb; kinds include common and proper nouns, count and mass nouns, and concrete and abstract nouns.

What it is for: Naming entities in language.

It can be identify nouns and their types; form plurals and cases; handle gender and articles; support tagging in software.

Distinguishing features

Names entities

Heads noun phrases

Inflects for number, case or gender in many languages

Open word class

What it looks like

Words in text and speech.

How it is recognised

Can take articles and plurals in many languages

Capitalised in German and for proper nouns in English

Nominal adjectives blur the line

Related models

is a kind of - category

word

heads - syntax

noun phrase

undergoes - morphology

inflection

is related to - proper nouns

name

In practice

Families and kinds

common nouns

proper nouns

count and mass nouns

abstract and concrete nouns

collective nouns

Standards and regulation

Universal Dependencies part-of-speech tags

Failure modes and hazards

Mis-tagging nouns used as adjectives

Ignoring language differences

Also called

metasyntactic variableethnonymsocionymbionymbiblical proper namenominal adjective-mey nounnoun class 3 (Meinhof)noun class 4 (Meinhof)noun class 1 (Meinhof)noun class 2 (Meinhof)noun class 5 (Meinhof)noun class 6 (Meinhof)noun class 7 (Meinhof)noun class 8 (Meinhof)noun class 9 (Meinhof)noun class 10 (Meinhof)noun class 11 (Meinhof)noun class 14 (Meinhof)noun class 15 (Meinhof)noun class 12 (Meinhof)noun class 13 (Meinhof)deverbal nounPunjabi nounfood nounArabic nounEgyptian Arabic nounlocaliserSindhi nounnoun often attributiveEnglish nounBhojpuri nounGe'ez nounnumeral nounsingulative nounnoun class 20 (Meinhof)noun class 21 (Meinhof)transitive nounlocative nounpersonal noun

+106

Where this came from

wikidata · CC0 1.0

Source repository Registry entry point

Drafted structure

Bundle to layer to finding to question, as the second pass will find it: 4 bundles · 8 layers · 8 findings · 16 questions.

Type Which noun.

Types differ.

Kind

Common or proper.

Kind

Noun type.

  1. Is this a common or proper, count or mass noun? definition
  2. How does that affect usage? definition

Identify

Tests.

Identify

Identification.

  1. Is this word functioning as a noun in this sentence? boundary
  2. Which test shows it? action
Grammar Forms.

Forms vary by language.

Plural

Number.

Plural

Plural forms.

  1. What is the plural form, and is it irregular? definition
  2. Which reference confirms it? provenance

Gender and case

Agreement.

Gender and case

Gender and case.

  1. What gender or case does the noun take here? provenance
  2. Which article agrees with it? definition
Writing Usage.

Usage guides help.

Style

Clarity.

Style

Style.

  1. Would a verb be clearer than a noun phrase here? action
  2. Which style guide applies? provenance

Capitalisation

Rules.

Capitalisation

Capitalisation.

  1. Should this noun be capitalised in this language? provenance
  2. Is it a proper noun? boundary
Technology Tagging.

Software tags nouns.

Tagging

POS tags.

Tagging

Part-of-speech tagging.

  1. How do taggers label this noun? provenance
  2. How accurate are they? measurement

Learning

Teaching.

Learning

Teaching.

  1. Which examples help learners recognise nouns? action
  2. Which errors are common? boundary

What the second pass must settle

  • Should noun types be separate entries?
  • How should language-specific rules be linked?
  • How should proper names be handled?
Draft as JSON