Triple

T11009114
Position Surface form Disambiguated ID Type / Status
Subject Tonight and Every Night E260200 entity
Predicate screenwriter P2831 FINISHED
Object Abem Finkel E529570 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: Abem Finkel | Statement: [Tonight and Every Night, screenwriter, Abem Finkel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abem Finkel
Context triple: [Tonight and Every Night, screenwriter, Abem Finkel]
  • A. Abem Finkel chosen
    Abem Finkel was an American screenwriter active during Hollywood’s early sound era, known for contributing to several notable films of the 1930s and 1940s.
  • B. Jules Fisher
    Jules Fisher is a renowned American theatrical lighting designer celebrated for his work on numerous Broadway productions and multiple Tony Award wins.
  • C. Ben Finkel
    Ben Finkel is a technology entrepreneur best known as the co-founder of the Q&A app Jelly and for his work in the startup and software development space.
  • D. Delice Burhans
    Delice Burhans was the wife of Willis Van Devanter, an Associate Justice of the United States Supreme Court in the early 20th century.
  • E. Max Fischer
    Max Fischer is an eccentric, overachieving yet academically struggling prep-school student whose obsessive involvement in extracurricular activities drives the offbeat coming-of-age story in the film "Rushmore."
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7978810208190b8e2966ae67b6314 completed April 9, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69e37498b9fc8190860acede4f49ea4a completed April 18, 2026, 12:10 p.m.
Created at: April 8, 2026, 9:25 p.m.