Triple

T7737191
Position Surface form Disambiguated ID Type / Status
Subject Terrell Municipal Airport E175412 entity
Predicate owner P347 FINISHED
Object City of Terrell E243614 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: City of Terrell | Statement: [Terrell Municipal Airport, owner, City of Terrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Terrell
Context triple: [Terrell Municipal Airport, owner, City of Terrell]
  • A. City of Terrell Hills
    The City of Terrell Hills is a small, affluent residential municipality located within the San Antonio metropolitan area in Bexar County, Texas.
  • B. Terrell, Texas chosen
    Terrell, Texas is a small city in North Texas known for its historic downtown, proximity to Dallas, and role as a regional commercial and educational hub.
  • C. City of Lamar
    City of Lamar is a municipal government in Lamar, Colorado, responsible for providing local services, infrastructure, and governance to the community.
  • D. Tarleton village
    Tarleton village is a rural community in Lancashire, England, known for its agricultural surroundings and location near key regional road links.
  • E. Pecan Hill, Texas
    Pecan Hill, Texas is a small rural city located in Ellis County within the Dallas–Fort Worth metropolitan area.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7035a97688190bf93efeee2e365ec completed March 27, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be3958ac8190a48ba07bd8ea3251 completed March 29, 2026, 5:52 a.m.
Created at: March 27, 2026, 4:07 p.m.