Triple

T15596131
Position Surface form Disambiguated ID Type / Status
Subject San Francisco (Be Sure to Wear Flowers in Your Hair) E374894 entity
Predicate writer P1360 FINISHED
Object John Phillips E470768 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: John Phillips | Statement: [San Francisco (Be Sure to Wear Flowers in Your Hair), writer, John Phillips]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Phillips
Context triple: [San Francisco (Be Sure to Wear Flowers in Your Hair), writer, John Phillips]
  • A. John Phillips
    John Phillips is a screenwriter best known for co-writing the 2023 comedy film "No Hard Feelings" starring Jennifer Lawrence.
  • B. John Phillips
    John Phillips was a physician and medical leader best known as one of the founders of the Cleveland Clinic, a major academic medical center in the United States.
  • C. John Phillips chosen
    John Phillips was an American singer, guitarist, and songwriter best known as the leader of the 1960s folk-rock group The Mamas & the Papas.
  • D. John Phillips
    John Phillips is a musician best known as a member of the Australian ambient/world music band Not Drowning, Waving.
  • E. John Phillips
    John Phillips was an actor known for his role in the British horror film "The Mummy’s Shroud."
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e5f9db8819083abf80f01f32b3d completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ecba8d08190998fc0688663a328 completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:12 a.m.