Triple

T3316469
Position Surface form Disambiguated ID Type / Status
Subject Bill Condon E69692 entity
Predicate screenwriterFor P25235 FINISHED
Object Kinsey E178795 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: Kinsey | Statement: [Bill Condon, screenwriterFor, Kinsey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kinsey
Context triple: [Bill Condon, screenwriterFor, Kinsey]
  • A. Kinsey chosen
    Kinsey is a 2004 biographical drama film about pioneering sex researcher Alfred Kinsey, starring Liam Neeson in the title role.
  • B. Blakely
    Blakely is a given name and surname of English origin that has become popular as a modern unisex first name.
  • C. Dr. Madden
    Dr. Madden is the psychiatrist in the rock musical "Next to Normal," who treats Diana Goodman and represents the medical approach to her mental illness.
  • D. Keeler
    Keeler is a surname most notably associated with James Edward Keeler, an American astronomer known for his pioneering work on Saturn's rings and spectroscopy.
  • E. Kean
    Kean is a stage musical about the life of 19th-century English actor Edmund Kean, known for its dramatic exploration of theatrical fame and personal turmoil.
  • 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_69ad85a0bb048190a5458d2738012d61 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb11230b881908f5b554323729cc5 completed March 8, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3250c720c81908a8a6fed9a6fd349 completed March 12, 2026, 8:41 p.m.
Created at: March 8, 2026, 3:11 p.m.