Triple

T4286338
Position Surface form Disambiguated ID Type / Status
Subject John Harbison E97277 entity
Predicate familyName P18 FINISHED
Object Harbison E97277 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: Harbison | Statement: [John Harbison, familyName, Harbison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harbison
Context triple: [John Harbison, familyName, Harbison]
  • A. Harbison chosen
    Harbison is a surname most notably associated with American composer John Harbison, known for his contributions to contemporary classical music.
  • B. Hayes
    Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
  • C. Hayes
    Hayes is a suburban town in west London, England, known for its residential areas, transport links, and proximity to Heathrow Airport.
  • D. McCauley
    McCauley is the maiden surname of Rosa Parks, the prominent American civil rights activist known for her pivotal role in the Montgomery bus boycott.
  • E. Hoyt
    Hoyt is a family surname of English origin borne by various notable individuals, including Mary Hoyt Sherman before her marriage.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3505d23d88190a638f2cc2acee9ee completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7c657b08190b96135c34622e559 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:08 p.m.