Triple

T8738007
Position Surface form Disambiguated ID Type / Status
Subject Walter Matthau E207432 entity
Predicate awardReceivedForWork P107 FINISHED
Object The Fortune Cookie E101034 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: The Fortune Cookie | Statement: [Walter Matthau, awardReceivedForWork, The Fortune Cookie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Fortune Cookie
Context triple: [Walter Matthau, awardReceivedForWork, The Fortune Cookie]
  • A. The Fortune Cookie chosen
    The Fortune Cookie is a 1966 American comedy film starring Jack Lemmon and Walter Matthau, notable as their first on-screen pairing and for its blend of sharp wit and social satire.
  • B. The Pie
    The Pie is the spirited horse ridden by Velvet Brown in the classic novel and film "National Velvet."
  • C. Yo! Sushi
    Yo! Sushi is a UK-based restaurant chain known for its conveyor-belt served Japanese-inspired dishes, particularly sushi.
  • D. Las Galletas
    Las Galletas is a small coastal resort town in southern Tenerife, Spain, known for its fishing harbor, relaxed atmosphere, and oceanfront promenades.
  • E. The Chinese Restaurant
    "The Chinese Restaurant" is a celebrated episode of the sitcom *Seinfeld* that exemplifies the show's "show about nothing" style by focusing entirely on the characters waiting for a table at a Chinese restaurant.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d470c8c81909ead395ef704c6ba completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf517c6fac8190b782c8f441635814 completed April 3, 2026, 5:34 a.m.
Created at: March 30, 2026, 6:38 p.m.