Triple

T1760113
Position Surface form Disambiguated ID Type / Status
Subject Clare Boothe Luce E38637 entity
Predicate givenName P17 FINISHED
Object Clare E126371 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: Clare | Statement: [Clare Boothe Luce, givenName, Clare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clare
Context triple: [Clare Boothe Luce, givenName, Clare]
  • A. Clare chosen
    Clare is a central character in the Restoration comedy "The Witty Fair One," known for embodying the play’s themes of wit, romance, and social intrigue.
  • B. Clare West
    Clare West was an early Hollywood costume designer known for her influential work on major silent films, including collaborations with director Cecil B. DeMille.
  • C. Erin
    Erin Jobs is the daughter of Apple co-founder Steve Jobs and his wife Laurene Powell Jobs.
  • D. Niles
    Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
  • E. Bethany
    Bethany is a village near Jerusalem mentioned in the New Testament, traditionally known as the home of Mary, Martha, and Lazarus and a frequent place visited by Jesus.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa643f6a188190a250d5982badcce5 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0ec80f48190bcdc92e5ed4e44e6 completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.