Triple

T9756743
Position Surface form Disambiguated ID Type / Status
Subject Earl Bakken E236571 entity
Predicate coFounderOf P104 FINISHED
Object Medtronic E7950 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: Medtronic | Statement: [Earl Bakken, coFounderOf, Medtronic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medtronic
Context triple: [Earl Bakken, coFounderOf, Medtronic]
  • A. Medtronic chosen
    Medtronic is a global medical technology company known for developing and manufacturing devices and therapies to treat a wide range of chronic diseases and conditions.
  • B. Boston Scientific
    Boston Scientific is a global medical technology company known for developing and manufacturing minimally invasive medical devices, particularly in cardiology and other interventional specialties.
  • C. Edwards Lifesciences
    Edwards Lifesciences is a global medical technology company best known for its innovations in heart valves and critical care monitoring systems.
  • D. Hospira
    Hospira is a pharmaceutical and medical device company known for its injectable drugs, infusion technologies, and biosimilars, operating as a subsidiary of Pfizer.
  • E. Abbott Vascular
    Abbott Vascular is a medical device division of Abbott Laboratories that specializes in cardiovascular products such as stents, catheters, and other vascular intervention technologies.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9fb2889481908fba4a449d5007fe completed April 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcdbdbcc8190b2c454729a50f7fb completed April 5, 2026, 1:37 a.m.
Created at: March 30, 2026, 8:24 p.m.