Triple

T20007408
Position Surface form Disambiguated ID Type / Status
Subject Velvet E494493 entity
Predicate hasSpinOff P7226 FINISHED
Object Velvet Colección 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: Velvet Colección | Statement: [Velvet, hasSpinOff, Velvet Colección]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velvet Colección
Context triple: [Velvet, hasSpinOff, Velvet Colección]
  • A. Velvet
    Velvet is a spy thriller comic book series written by Ed Brubaker that follows a veteran female secret agent drawn back into the world of espionage.
  • B. Velvet chosen
    Velvet is a Spanish romantic drama television series set in a 1950s fashion house, focusing on the love story between a seamstress and the heir to the business.
  • C. Velvet
    Velvet is a studio album by American singer Adam Lambert that showcases his blend of glam rock, pop, and soulful retro influences.
  • D. Velvet Crush
    Velvet Crush is an American power pop band known for its jangly guitars, melodic songwriting, and strong ties to the 1990s alternative rock and indie scenes.
  • E. Velvet and Silk City
    Velvet and Silk City is a traditional nickname for Krefeld, a German city historically renowned for its textile and silk manufacturing industry.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a648a88190853ee741edcf6ca2 completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:33 p.m.