Triple

T8156138
Position Surface form Disambiguated ID Type / Status
Subject Page Eight E190453 entity
Predicate castMember P1668 FINISHED
Object Tom Hughes E709202 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: Tom Hughes | Statement: [Page Eight, castMember, Tom Hughes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Hughes
Context triple: [Page Eight, castMember, Tom Hughes]
  • A. Tom Hughes chosen
    Tom Hughes is a British actor known for his roles in film and television, including period dramas and contemporary comedies.
  • B. Ron Hutchinson
    Ron Hutchinson is a Northern Irish playwright and screenwriter known for his work in film and television, including adaptations and genre projects in Hollywood.
  • C. Bob Scott
    Bob Scott was an Australian rules football field umpire best known for officiating the 1934 Victorian Football League Grand Final.
  • D. Harry Bright
    Harry Bright is one of the three possible fathers and central adult characters in the musical and film "Mamma Mia!", known for his reserved, uptight demeanor that contrasts with the story’s exuberant Greek-island setting.
  • E. Dan Hughes
    Dan Hughes is an American basketball coach best known for leading the WNBA’s Seattle Storm to a championship and for his long, successful career coaching multiple WNBA franchises.
  • 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb44d8a37481909397b5cc321b94be completed March 31, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cced43a5448190b2600cbdbabf9d31 completed April 1, 2026, 10:02 a.m.
Created at: March 30, 2026, 5:37 p.m.