Triple

T13975514
Position Surface form Disambiguated ID Type / Status
Subject Halt and Catch Fire E336177 entity
Predicate executiveProducer P7225 FINISHED
Object Mark Johnson E275841 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: Mark Johnson | Statement: [Halt and Catch Fire, executiveProducer, Mark Johnson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Johnson
Context triple: [Halt and Catch Fire, executiveProducer, Mark Johnson]
  • A. Mark Johnson chosen
    Mark Johnson is an American film and television producer best known for his work on acclaimed projects such as the series Breaking Bad.
  • B. Mark Johnson
    Mark Johnson is an American ice hockey player best known as a leading scorer and key figure in the "Miracle on Ice" U.S. team that won gold at the 1980 Winter Olympics.
  • C. Matt Johnson
    Matt Johnson is a screenwriter best known for his work on the action-thriller film "Into the Blue."
  • D. Norm Johnson
    Norm Johnson was a prominent ice hockey player best known for his standout performances with the Portland Buckaroos in the Western Hockey League.
  • E. Greg Johnson
    Greg Johnson is a television writer and producer best known for co-creating the animated series "Pacific Rim: The Black" and his work on various Marvel animated shows.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e90dc148190b38e339aac0de484 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1e1eb108190b3c0739b94556172 completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:18 p.m.