Triple

T22589524
Position Surface form Disambiguated ID Type / Status
Subject Easterwood Airport E564903 entity
Predicate serves P98 FINISHED
Object College Station, Texas NE NERFINISHED

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: College Station, Texas | Statement: [Easterwood Airport, serves, College Station, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: College Station, Texas
Context triple: [Easterwood Airport, serves, College Station, Texas]
  • A. College Station, Texas chosen
    College Station, Texas is a central Texas city best known as the home of Texas A&M University and its large student-centered community.
  • B. Prairie View, Texas
    Prairie View, Texas is a small city in Waller County best known as the home of Prairie View A&M University and as part of the greater Houston metropolitan region.
  • C. North Lake College Station
    North Lake College Station is a Dallas Area Rapid Transit (DART) light rail stop serving the North Lake College area in Irving, Texas.
  • D. Aggieville
    Aggieville is a historic entertainment and shopping district in Manhattan, Kansas, known for its bars, restaurants, and proximity to Kansas State University.
  • E. San Marcos, Texas
    San Marcos, Texas is a central Texas city along the San Marcos River known for its university campus, outlet shopping, and outdoor recreation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245836014819091b91ed3074742a3 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1615f63788190acf776b313f0794a completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 2:48 p.m.