Triple

T1491078
Position Surface form Disambiguated ID Type / Status
Subject Someone Comes to Town, Someone Leaves Town E29579 entity
Predicate hasUrbanSetting P17246 FINISHED
Object yes LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: yes | Statement: [Someone Comes to Town, Someone Leaves Town, hasUrbanSetting, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUrbanSetting
Context triple: [Someone Comes to Town, Someone Leaves Town, hasUrbanSetting, yes]
  • A. hasUrbanFeature
    Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
  • B. hasUrbanFunction
    Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
  • C. isUrbanized chosen
    Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
  • D. containsUrbanArea
    Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
  • E. hasUrbanRole
    Indicates that an entity plays a specific functional or social role within an urban or city context.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a498da82e08190ba833330d05f380f completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6c3ace4819081bc2b86ee2486b6 completed March 1, 2026, 11:07 p.m.
PD Predicate disambiguation batch_69a4c48902808190a8028d359bcf123e completed March 1, 2026, 10:58 p.m.
Created at: March 1, 2026, 8:12 p.m.