Triple

T6219690
Position Surface form Disambiguated ID Type / Status
Subject Royce Gracie E139077 entity
Predicate fought P30824 FINISHED
Object Matt Hughes E213615 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: Matt Hughes | Statement: [Royce Gracie, fought, Matt Hughes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Hughes
Context triple: [Royce Gracie, fought, Matt Hughes]
  • A. Matt Hughes chosen
    Matt Hughes is a retired American mixed martial artist widely regarded as one of the greatest welterweights in UFC history, known for his dominant wrestling and multiple championship reigns.
  • B. Jimmy Hughes
    Jimmy Hughes is a central character on the sitcom "Yes, Dear," portrayed as a well-meaning but often overwhelmed young father and husband navigating everyday family chaos.
  • C. Aaron Hughes
    Aaron Hughes is a retired Northern Irish defender known for his long, consistent club career in the English Premier League and his record number of caps for the Northern Ireland national team.
  • D. Matt Hulett
    Matt Hulett is an American technology and business executive known for leading and scaling multiple software and digital media companies.
  • E. Kevin Hageman
    Kevin Hageman is an American screenwriter and producer known for his work on animated and family films and television series, including contributions to The Lego Movie franchise.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062bbb768819099402d367f124639 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5190757648190a73575e680a35684 completed March 26, 2026, 11:31 a.m.
Created at: March 22, 2026, 4:21 p.m.