Triple

T19436189
Position Surface form Disambiguated ID Type / Status
Subject Healthy Planet E486229 entity
Predicate integratesWith P1075 FINISHED
Object Epic EHR 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: Epic EHR | Statement: [Healthy Planet, integratesWith, Epic EHR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Epic EHR
Context triple: [Healthy Planet, integratesWith, Epic EHR]
  • A. 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.
  • B. Epic Systems chosen
    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. NextGen Healthcare
    NextGen Healthcare is a U.S.-based health IT company that provides electronic health record, practice management, and related software solutions for medical practices and healthcare organizations.
  • D. Cerner
    Cerner is a major American health information technology company best known for its electronic health record (EHR) systems and healthcare data solutions.
  • E. MEDITECH
    MEDITECH is a healthcare information technology company best known for providing electronic health record (EHR) and hospital information systems to healthcare organizations.
  • 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6336001488190a05f372779711ed2 completed April 20, 2026, 2:08 p.m.
Created at: April 10, 2026, 1:38 p.m.