Triple

T875616
Position Surface form Disambiguated ID Type / Status
Subject SNOMED CT E18910 entity
Predicate relatedStandard P37 FINISHED
Object HL7 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: HL7 FHIR | Statement: [SNOMED CT, relatedStandard, HL7 FHIR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HL7 FHIR
Context triple: [SNOMED CT, relatedStandard, HL7 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. Health Connect
    Health Connect is a unified health and fitness data platform on Android that lets apps securely share and manage users’ wellness information in one place.
  • C. 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.
  • 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. IHE Patient Care Device profiles
    IHE Patient Care Device profiles are interoperability specifications that define how medical devices integrate and exchange data within healthcare IT systems to support safe, coordinated patient care.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4acae12948190923d31966c26a130 completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b8520a008190a15bdb93e8ce2438 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:39 p.m.