Triple

T3216012
Position Surface form Disambiguated ID Type / Status
Subject Dan Aykroyd E67395 entity
Predicate characterPortrayed P1507 FINISHED
Object Ray Stantz E294658 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: Ray Stantz | Statement: [Dan Aykroyd, characterPortrayed, Ray Stantz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray Stantz
Context triple: [Dan Aykroyd, characterPortrayed, Ray Stantz]
  • A. Martin Brody
    Martin Brody is the cautious, duty-driven police chief of Amity Island who becomes the central human protagonist battling the great white shark in the film "Jaws."
  • B. Egon
    Egon is a masculine given name of German origin, notably borne by several European politicians, artists, and intellectuals.
  • C. Dr. Egon Spengler chosen
    Dr. Egon Spengler is the bespectacled, scientifically minded Ghostbuster and paranormal researcher from the "Ghostbusters" film franchise.
  • D. Buford "Mad Dog" Tannen
    Buford "Mad Dog" Tannen is the ruthless, hot-tempered outlaw and ancestor of Biff Tannen who serves as the main antagonist in the Old West setting of Back to the Future Part III.
  • E. Silas Laurence Loomis
    Silas Laurence Loomis was a 19th-century American physician, inventor, and educator known for his contributions to medical science and technological innovation.
  • 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_69ad858b8adc8190ad989712c87a476b completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adab096b588190b22e41a76263ae92 completed March 8, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2623c90cc819085a94adfe3eb3f3f completed March 12, 2026, 6:50 a.m.
Created at: March 8, 2026, 3:07 p.m.