Triple

T13709523
Position Surface form Disambiguated ID Type / Status
Subject Bull Durham E328732 entity
Predicate productionCompany P490 FINISHED
Object Mount Company E55592 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: Mount Company | Statement: [Bull Durham, productionCompany, Mount Company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Company
Context triple: [Bull Durham, productionCompany, Mount Company]
  • A. Mount Company chosen
    Mount Company is a film production company best known for producing the 1988 baseball romantic comedy "Bull Durham."
  • B. John Company
    John Company is a historical nickname for the British East India Company, the powerful trading corporation that played a central role in establishing British rule in India.
  • C. United Company
    United Company was a prominent late 17th-century London theatre company formed by the merger of the King’s Company and the Duke’s Company, active during the Restoration period.
  • D. Martin Company
    Martin Company was a major American aerospace and defense contractor known for developing missiles, spacecraft, and military systems before merging into Lockheed Martin.
  • E. Marcus Corporation
    Marcus Corporation is a U.S.-based company best known for its movie theatre and hospitality businesses, including operating cinema chains and hotels.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd43949e6c8190ae5e4fa119cde33a completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d52b3708190ae0945e65b271556 completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:54 p.m.