Triple

T16689285
Position Surface form Disambiguated ID Type / Status
Subject Hill County E405550 entity
Predicate hasSettlement P1068 FINISHED
Object Abbott, Texas E320693 NE 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: Abbott, Texas | Statement: [Hill County, hasSettlement, Abbott, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abbott, Texas
Context triple: [Hill County, hasSettlement, Abbott, Texas]
  • A. Abbott, Texas chosen
    Abbott, Texas is a small rural town in Hill County best known as the birthplace of country music legend Willie Nelson.
  • B. Aubrey, Texas
    Aubrey, Texas is a small town in Denton County known for its rural charm, horse ranches, and proximity to the Dallas–Fort Worth metroplex.
  • C. Taft, Texas
    Taft, Texas is a small city in San Patricio County that functions as part of the greater Corpus Christi metropolitan region in South Texas.
  • D. Stinnett, Texas
    Stinnett, Texas is a small city in the Texas Panhandle that serves as an administrative and service hub for the surrounding rural area.
  • E. Aquilla, Texas
    Aquilla, Texas is a small rural town in central Texas known for its close-knit community and proximity to Aquilla Lake.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea80d88819091fc61ed3c01955a completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a46a4cc8190b47f9dcf27380c46 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.