Triple

T9430286
Position Surface form Disambiguated ID Type / Status
Subject Dick Wolf E227355 entity
Predicate employer P7 FINISHED
Object Wolf Entertainment E653941 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: Wolf Entertainment | Statement: [Dick Wolf, employer, Wolf Entertainment]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolf Entertainment
Context triple: [Dick Wolf, employer, Wolf Entertainment]
  • A. Wolf Entertainment chosen
    Wolf Entertainment is an American television production company founded by producer Dick Wolf, best known for creating and overseeing the long-running Law & Order and Chicago franchise series.
  • B. Ludicorp
    Ludicorp was a Canadian software company best known for creating the photo-sharing service Flickr before being acquired by Yahoo.
  • C. Wolf Den
    Wolf Den is a live entertainment venue located within the Mohegan Sun casino resort, known for hosting free concerts and performances.
  • D. Wolf Den
    Wolf Den is a notable rocky cave and historic landmark within Mashamoquet State Park in Connecticut, traditionally associated with early colonial wolf-hunting legends.
  • E. Desert Wolf Productions
    Desert Wolf Productions is a television production company best known for its work on the horror drama series "Penny Dreadful."
  • 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_69ca8436ba308190903e470776d2d893 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e5ed7408190beda5fb078e9345a completed April 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d11038f7b88190bd6b895f5544c63e completed April 4, 2026, 1:20 p.m.
Created at: March 30, 2026, 7:49 p.m.