Triple

T2798731
Position Surface form Disambiguated ID Type / Status
Subject Handler E53099 entity
Predicate hasNotableBearer P458 FINISHED
Object Philip Handler E8123 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: Philip Handler | Statement: [Handler, hasNotableBearer, Philip Handler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philip Handler
Context triple: [Handler, hasNotableBearer, Philip Handler]
  • A. Philip Handler chosen
    Philip Handler was an influential American biochemist and longtime president of the U.S. National Academy of Sciences, recognized for his leadership in science policy and public service.
  • B. Philip Brenner
    Philip Brenner is a scholar and author known for his work on U.S. foreign policy and Latin American studies, often collaborating with historian James G. Blight.
  • C. Pandro S. Berman
    Pandro S. Berman was a prominent American film producer of Hollywood’s classic era, known for overseeing numerous successful MGM and RKO pictures.
  • D. Philip Brownstein
    Philip Brownstein was a professional basketball coach best known for leading the early NBA-era Chicago Stags franchise.
  • E. Philip Bruns
    Philip Bruns was an American character actor best known for his television and film roles in the 1970s and 1980s, including his work on the satirical soap opera "Mary Hartman, Mary Hartman."
  • 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_69ab495a90788190941b6917e1eca3a6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abddf31eec8190a898713e53d1aa5c completed March 7, 2026, 8:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5627344648190b2794d4e71524bf4 completed March 14, 2026, 1:28 p.m.
Created at: March 6, 2026, 9:58 p.m.