Triple

T8122654
Position Surface form Disambiguated ID Type / Status
Subject Madness E189644 entity
Predicate hasMember P10 FINISHED
Object Suggs E345203 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: Suggs | Statement: [Madness, hasMember, Suggs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suggs
Context triple: [Madness, hasMember, Suggs]
  • A. Suggs chosen
    Suggs is a surname shared by various notable individuals across fields such as sports, music, and entertainment.
  • B. Simon Ward
    Simon Ward was a British actor known for his roles in films such as "Young Winston," "The Three Musketeers," and numerous stage and television productions.
  • C. Sam Mills
    Sam Mills was a standout undersized linebacker and team leader in the NFL, best known for his Pro Bowl play and inspirational presence with the New Orleans Saints and Carolina Panthers.
  • D. Stuart Maynard
    Stuart Maynard is an English football manager best known for managing Notts County F.C. in the lower tiers of the English football league system.
  • E. Toby Sedgwick
    Toby Sedgwick is a British movement director, actor, and choreographer known for his innovative physical theatre work on major stage productions, including the National Theatre’s "Frankenstein" and the original production of "War Horse."
  • 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_69ca82bb74848190afb1f18640632c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb435cb30881909ccaa2f625e53799 completed March 31, 2026, 3:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc945c743c8190bf1d8e60975bd8bc completed April 1, 2026, 3:43 a.m.
Created at: March 30, 2026, 5:33 p.m.