Triple

T5017620
Position Surface form Disambiguated ID Type / Status
Subject CERN E112771 entity
Predicate represents P129 FINISHED
Object Cerner Corporation E20635 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: Cerner Corporation | Statement: [CERN, represents, Cerner Corporation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cerner Corporation
Context triple: [CERN, represents, Cerner Corporation]
  • A. Cerner chosen
    Cerner is a major American health information technology company best known for its electronic health record (EHR) systems and healthcare data solutions.
  • B. Epic Systems
    Epic Systems is a leading American healthcare software company best known for its widely used electronic health record (EHR) systems in hospitals and clinics.
  • C. HCA Healthcare
    HCA Healthcare is a large American for-profit healthcare company that operates a nationwide network of hospitals and healthcare facilities.
  • D. Allscripts
    Allscripts is a healthcare information technology company known for providing electronic health record (EHR), practice management, and related software solutions to hospitals and physician practices.
  • E. Athenahealth
    Athenahealth is a U.S.-based healthcare technology company that provides cloud-based electronic health record, practice management, and revenue cycle management solutions for medical practices and health systems.
  • 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_69bd4434acb8819086679dbeccc2fe54 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd734037a88190a950db814412a023 completed March 20, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c5e06fc8190bdd875c04cefd789 completed March 21, 2026, 1:25 p.m.
Created at: March 20, 2026, 1:35 p.m.