Triple

T19886107
Position Surface form Disambiguated ID Type / Status
Subject Claremont McKenna College E477903 entity
Predicate cityServed P82 FINISHED
Object Claremont 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: Claremont | Statement: [Claremont McKenna College, cityServed, Claremont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Claremont
Context triple: [Claremont McKenna College, cityServed, Claremont]
  • A. Claremont
    Claremont is a residential neighbourhood within the city of Pickering in Ontario, Canada.
  • B. Claremont
    Claremont is a historic country house and estate in Surrey, England, known for its landscaped gardens and royal connections.
  • C. Claremont chosen
    Claremont is a small, affluent college town in eastern Los Angeles County, California, known for its consortium of higher education institutions collectively called the Claremont Colleges.
  • D. Claremont
    Claremont is a residential neighborhood in the Bronx, New York City, known for its dense urban character and proximity to major subway lines.
  • E. Claremont
    Claremont is a suburb of Hobart in Tasmania, Australia, known for its residential character and proximity to the Derwent River.
  • 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65909fe0481908e22b60d04fe2b11 completed April 20, 2026, 4:49 p.m.
Created at: April 10, 2026, 1:52 p.m.