Triple

T5029232
Position Surface form Disambiguated ID Type / Status
Subject Allscripts E113253 entity
Predicate supportsStandard P1587 FINISHED
Object FHIR E6183 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: FHIR | Statement: [Allscripts, supportsStandard, FHIR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FHIR
Context triple: [Allscripts, supportsStandard, FHIR]
  • A. HL7 standards chosen
    HL7 standards are a widely adopted set of international specifications for the exchange, integration, sharing, and retrieval of electronic health information between healthcare systems.
  • B. HL7 International
    HL7 International is a global standards organization that develops and promotes frameworks and specifications for the exchange, integration, sharing, and retrieval of electronic health information.
  • C. OpenMRS
    OpenMRS is an open-source medical record system platform widely used in resource-constrained settings to improve healthcare delivery and data management.
  • D. SNOMED CT
    SNOMED CT is a comprehensive, multilingual clinical healthcare terminology used worldwide to standardize the recording and sharing of medical information in electronic health records.
  • E. SNOMED International
    SNOMED International is a global not-for-profit organization responsible for developing and promoting the SNOMED CT clinical terminology standard used in healthcare systems worldwide.
  • 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.