Triple

T24700277
Position Surface form Disambiguated ID Type / Status
Subject Kaufman, Texas E611715 entity
Predicate hasUrbanCoreProximity P44123 FINISHED
Object Dallas–Fort Worth urban core 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: Dallas–Fort Worth urban core | Statement: [Kaufman, Texas, hasUrbanCoreProximity, Dallas–Fort Worth urban core]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUrbanCoreProximity
Context triple: [Kaufman, Texas, hasUrbanCoreProximity, Dallas–Fort Worth urban core]
  • A. hasUrbanProximity chosen
    Indicates that one entity is located near or within easy access to an urban area associated with another entity.
  • B. hasUrbanAreaApprox
    Indicates an approximate measure or estimate of the size or extent of an entity’s urban area.
  • C. isUrbanizedAround
    Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
  • D. connectsToUrbanCenter
    Indicates that one entity has a direct or functional linkage to an urban center, such as through infrastructure, services, or regular interaction.
  • E. isUrbanAxisNear
    Indicates that one urban axis (such as a main street or corridor) is located in close spatial proximity to another reference feature or axis within an urban area.
  • 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_69e2c4d76d148190b58ad612467149a5 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f422aee0408190899efe7e24ef2b40 completed May 1, 2026, 3:49 a.m.
PD Predicate disambiguation batch_69f420e92cc88190a803aecdae78a051 completed May 1, 2026, 3:41 a.m.
Created at: April 18, 2026, 3:22 a.m.