Triple

T20855607
Position Surface form Disambiguated ID Type / Status
Subject Don Mitchell E513470 entity
Predicate notableWork P4 FINISHED
Object Ironside 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: Ironside | Statement: [Don Mitchell, notableWork, Ironside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ironside
Context triple: [Don Mitchell, notableWork, Ironside]
  • A. Ironside chosen
    Ironside is an American television crime drama series centered on a paraplegic chief of detectives who solves cases from his wheelchair.
  • B. Ironside
    Ironside is the epithet of Edmund Ironside, an early 11th-century English king renowned for his resilience and military resistance against Viking invaders.
  • C. Ironsides
    Ironsides were the disciplined, highly effective cavalry troops led by Oliver Cromwell during the English Civil War, renowned for their religious zeal and battlefield success.
  • D. The Wing
    The Wing was a women-focused co-working and community space network known for its stylish, inclusive hubs designed to support professional women and gender-expansive people.
  • E. The Sky Hawk
    The Sky Hawk is a 1929 American early sound aviation drama film notable for its World War I flying sequences and transitional use of both silent and talking scenes.
  • 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_69e0b4f5b01081909452f654d2fc3f50 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c3a81ac4819084a07625b8ed4ec5 completed April 21, 2026, 12:24 a.m.
Created at: April 16, 2026, 12:44 p.m.