Triple

T5029239
Position Surface form Disambiguated ID Type / Status
Subject Allscripts E113253 entity
Predicate competitor P1375 FINISHED
Object MEDITECH E114173 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: MEDITECH | Statement: [Allscripts, competitor, MEDITECH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MEDITECH
Context triple: [Allscripts, competitor, MEDITECH]
  • A. MEDITECH chosen
    MEDITECH is a healthcare information technology company best known for providing electronic health record (EHR) and hospital information systems to healthcare organizations.
  • B. Cerner
    Cerner is a major American health information technology company best known for its electronic health record (EHR) systems and healthcare data solutions.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd738f2cc88190a03eebf19e407411 completed March 20, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c6859a88190bbf5688812f2eb91 completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:36 p.m.