Triple

T20344390
Position Surface form Disambiguated ID Type / Status
Subject Tyco BMW E495826 entity
Predicate sponsors P1807 FINISHED
Object Tyco NE NERFINISHED

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: Tyco | Statement: [Tyco BMW, sponsors, Tyco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyco
Context triple: [Tyco BMW, sponsors, Tyco]
  • A. Tyco International chosen
    Tyco International was a multinational conglomerate known for its security systems, fire protection, and industrial products before being acquired by Johnson Controls.
  • B. Honeywell
    Honeywell is a multinational conglomerate best known for its aerospace systems, building technologies, performance materials, and industrial automation products.
  • C. Fortive
    Fortive is an American diversified industrial technology company that owns and operates a portfolio of measurement, automation, and industrial solutions businesses.
  • D. Guardian Industries
    Guardian Industries is a major global manufacturer of glass, automotive, and building products, known for its architectural and float glass operations.
  • E. Mitre Corporation
    Mitre Corporation is a not-for-profit organization that operates federally funded research and development centers, providing systems engineering and advanced technology support primarily to U.S. government agencies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a3320881909495ae8bc30bc2dc completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67837bef8819091e552d1c8a1665c completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:24 a.m.