Triple

T15378774
Position Surface form Disambiguated ID Type / Status
Subject Alex Gorsky E367742 entity
Predicate employer P7 FINISHED
Object Johnson & Johnson E8888 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: Johnson & Johnson | Statement: [Alex Gorsky, employer, Johnson & Johnson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johnson & Johnson
Context triple: [Alex Gorsky, employer, Johnson & Johnson]
  • A. Johnson & Johnson chosen
    Johnson & Johnson is a multinational healthcare conglomerate best known for its pharmaceuticals, medical devices, and consumer health products.
  • B. Abbott Laboratories
    Abbott Laboratories is a global healthcare company that develops and manufactures medical devices, diagnostics, branded generic medicines, and nutritional products.
  • C. Pharmaceutical Research and Manufacturers of America
    Pharmaceutical Research and Manufacturers of America is a major U.S. trade association representing leading biopharmaceutical and drug research companies.
  • D. A.H. Robins Company
    A.H. Robins Company was an American pharmaceutical and consumer products manufacturer best known for brands like ChapStick and Robitussin.
  • E. Merck & Co.
    Merck & Co. is a major American pharmaceutical company known for developing and producing vaccines, oncology drugs, and other innovative medicines.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e6044488190b0499db109f7f821 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b56dd1c81909a3933330e85fe0e completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:19 a.m.