Triple

T19266525
Position Surface form Disambiguated ID Type / Status
Subject Harvey Mudd College E481793 entity
Predicate city P40 FINISHED
Object Claremont
Claremont is a small, affluent college town in eastern Los Angeles County, California, best known for its cluster of prestigious institutions collectively called the Claremont Colleges.
 E844471 NE FINISHED

How this triple was built (4 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: [Harvey Mudd College, city, Claremont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Claremont
Context triple: [Harvey Mudd College, city, Claremont]
  • A. Claremont
    Claremont is a residential area within the City of Salford in Greater Manchester, England.
  • B. Claremont
    Claremont is a small town located in the rural interior of Saint Ann Parish on Jamaica’s north coast.
  • C. Claremont
    Claremont is a well-established residential and commercial suburb in Cape Town, South Africa, known for its shopping centers, schools, and proximity to the University of Cape Town.
  • D. Claremont
    Claremont is a suburb of Hobart in Tasmania, Australia, known for its residential character and proximity to the Derwent River.
  • E. Claremont
    Claremont is a residential neighbourhood within the city of Pickering in Ontario, Canada.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Claremont
Triple: [Harvey Mudd College, city, Claremont]
Generated description
Claremont is a small, affluent college town in eastern Los Angeles County, California, best known for its cluster of prestigious institutions collectively called the Claremont Colleges.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Claremont
Target entity description: Claremont is a small, affluent college town in eastern Los Angeles County, California, best known for its cluster of prestigious institutions collectively called the Claremont Colleges.
  • A. 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.
  • B. Claremont
    Claremont is a well-established residential and commercial suburb in Cape Town, South Africa, known for its shopping centers, schools, and proximity to the University of Cape Town.
  • C. Claremont
    Claremont is a small town located in the rural interior of Saint Ann Parish on Jamaica’s north coast.
  • D. Claremont
    Claremont is a historic country house and estate in Surrey, England, known for its landscaped gardens and royal connections.
  • E. Claremont
    Claremont is a residential neighbourhood within the city of Pickering in Ontario, Canada.
  • F. None of above.

Provenance (5 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_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fb8d58988190a942627b1fb79285 completed April 20, 2026, 10:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a07144768688190ab3c36d05b7d4e94 completed May 15, 2026, 12:40 p.m.
NEDg Description generation batch_6a0715514bac8190aafb36b96d4b167d completed May 15, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_6a07163cb15881908435e7d2fa68b06e completed May 15, 2026, 12:49 p.m.
Created at: April 10, 2026, 1:29 p.m.