Triple

T6546248
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Ferguson E151014 entity
Predicate notableWork P4 FINISHED
Object Silo E199126 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: Silo | Statement: [Rebecca Ferguson, notableWork, Silo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silo
Context triple: [Rebecca Ferguson, notableWork, Silo]
  • A. Silo chosen
    Silo is a dystopian science fiction television series in which David Oyelowo appears, set in an underground society governed by strict rules and secrets.
  • B. Milrow
    Milrow was a 1969 underground U.S. nuclear test conducted on Amchitka Island in Alaska as part of the Cold War weapons testing program.
  • C. La Pila
    La Pila is a small village on Elba Island in Tuscany, Italy, forming one of the hamlets of the municipality of Campo nell’Elba.
  • D. The Pit
    The Pit is a famed college basketball arena in Albuquerque, New Mexico, renowned for its intense atmosphere and distinctive sunken design.
  • E. Millarworld
    Millarworld is a creator-owned comic book imprint and shared universe founded by writer Mark Millar, known for titles like Kick-Ass, Wanted, and Kingsman: The Secret Service.
  • 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_69c687f3fd60819083bfa583e5bcfa71 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6adf00aa48190a86a9ad4795363d9 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d54b6d8c819083595375194aee12 completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:50 p.m.