Triple

T8958954
Position Surface form Disambiguated ID Type / Status
Subject Paul Gorup E213549 entity
Predicate notableWork P4 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: [Paul Gorup, notableWork, Cerner Corporation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cerner Corporation
Context triple: [Paul Gorup, notableWork, 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. 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.
  • E. 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.
  • 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_69ca8399ad2081909f8fa41d4314c215 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc672b12b48190a9d964f79b96d237 completed April 1, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc946a2f88190b7cd0fca67d31dfd completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 7 p.m.