Triple

T8454804
Position Surface form Disambiguated ID Type / Status
Subject Reveille E199893 entity
Predicate locatedIn P40 FINISHED
Object College Station, Texas E15336 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: College Station, Texas | Statement: [Reveille, locatedIn, College Station, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: College Station, Texas
Context triple: [Reveille, locatedIn, 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 (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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe48ca9988190b60ebd09a135194d completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce39caf4bc8190a1850b2124684a2a completed April 2, 2026, 9:41 a.m.
Created at: March 30, 2026, 6:10 p.m.