Triple

T21735444
Position Surface form Disambiguated ID Type / Status
Subject Excuse My French E536509 entity
Predicate hasGuestAppearance P4920 FINISHED
Object Red Cafe NE NERFINISHED

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: Red Cafe | Statement: [Excuse My French, hasGuestAppearance, Red Cafe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Cafe
Context triple: [Excuse My French, hasGuestAppearance, Red Cafe]
  • A. Red Café chosen
    Red Café is a Brooklyn-born American rapper known for his mixtapes, club anthems, and collaborations within the East Coast hip-hop scene.
  • B. Electric Café
    Electric Café is a studio album by American R&B/pop group En Vogue that marked their return with a contemporary, electronically influenced sound.
  • C. Electric Café
    Electric Café is a 1986 electronic music album by German band Kraftwerk that explores themes of digital communication and modern technology through minimalist, synth-driven soundscapes.
  • D. The Cafe
    The Cafe is a casual dining spot where people can relax, socialize, and enjoy beverages and light meals.
  • E. Border Cafe
    "Border Cafe" is a 1937 American Western film featuring Marjorie Lord in one of her early screen roles.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46d3284819099a4f9d5a704eb95 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69effd0b0da0819098ef03360eea6a0d completed April 28, 2026, 12:19 a.m.
Created at: April 16, 2026, 6:48 p.m.