Triple

T12509813
Position Surface form Disambiguated ID Type / Status
Subject Davis Diamond E299045 entity
Predicate city P40 FINISHED
Object College Station 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 | Statement: [Davis Diamond, city, College Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: College Station
Context triple: [Davis Diamond, city, College Station]
  • 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. 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.
  • C. Aggieville
    Aggieville is a historic entertainment and shopping district in Manhattan, Kansas, known for its bars, restaurants, and proximity to Kansas State University.
  • D. 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.
  • E. College Station, Arkansas
    College Station, Arkansas is a small census-designated community located in Pulaski County near Little Rock.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541c1ca08190a4026c394ebcbeb5 completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6685bafcc8190beae748d979762e1 completed May 2, 2026, 9:10 p.m.
Created at: April 8, 2026, 9:57 p.m.