Triple

T1596959
Position Surface form Disambiguated ID Type / Status
Subject Dracut E34304 entity
Predicate suburbanCharacter P9847 FINISHED
Object true 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: true | Statement: [Dracut, suburbanCharacter, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: suburbanCharacter
Context triple: [Dracut, suburbanCharacter, true]
  • A. hasSuburbanCharacter chosen
    Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
  • B. isSuburbanCommunityIn
    Indicates that a suburban community is located within or belongs to a specified larger geographic or administrative area.
  • C. hasSuburbanAreas
    Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
  • D. hasSuburbanSection
    Indicates that a larger route, line, or area includes a portion that passes through or serves a suburban region.
  • E. isSuburbanCityOf
    Indicates that one city is a suburban municipality that is part of, or closely associated with, a larger primary city or metropolitan 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a916d413f08190a4e137e5ed262e25 completed March 5, 2026, 5:38 a.m.
PD Predicate disambiguation batch_69a907bfb39c8190a31e0be14d3d52e6 completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:27 p.m.