Triple

T3527414
Position Surface form Disambiguated ID Type / Status
Subject Kevin Bacon E74573 entity
Predicate notableWork P4 FINISHED
Object Diner E356990 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: Diner | Statement: [Kevin Bacon, notableWork, Diner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diner
Context triple: [Kevin Bacon, notableWork, Diner]
  • A. Diner chosen
    Diner is a 1982 American coming-of-age comedy-drama film directed by Barry Levinson that follows a group of friends reuniting in 1959 Baltimore as they navigate adulthood, relationships, and changing times.
  • B. Mel’s Diner
    Mel’s Diner is a retro-themed American restaurant styled after a classic 1950s diner, known for serving burgers, fries, and milkshakes in a nostalgic setting.
  • C. Dockside Diner
    Dockside Diner is a casual, retro-themed quick-service restaurant located on the shores of Echo Lake in Disney’s Hollywood Studios.
  • D. Eater
    Eater is a science fiction novel by Gregory Benford that explores humanity’s encounter with a mysterious, sentient black hole-like entity.
  • E. Encounter Restaurant
    Encounter Restaurant was a futuristic-themed dining venue located inside Los Angeles International Airport’s iconic Theme Building, known for its space-age design and panoramic views.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc6d099c8190b2b1e65a56e52089 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bca41a88190b5550b9c1e763092 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:19 p.m.