Triple

T8521827
Position Surface form Disambiguated ID Type / Status
Subject IHE XCPD E201710 entity
Predicate fullName P16 FINISHED
Object Cross-Community Patient Discovery
Cross-Community Patient Discovery is an IHE profile that enables healthcare organizations in different communities or domains to locate and match patient records across disparate health information systems.
E738001 NE FINISHED

How this triple was built (4 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: Cross-Community Patient Discovery | Statement: [IHE XCPD, fullName, Cross-Community Patient Discovery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cross-Community Patient Discovery
Context triple: [IHE XCPD, fullName, Cross-Community Patient Discovery]
  • A. Centre for Collaboration with Digital Health Networks
    The Centre for Collaboration with Digital Health Networks is a unit within the Norwegian Institute of Public Health that focuses on coordinating and advancing partnerships and initiatives in digital health.
  • B. Centre for Collaboration with Registry Networks
    The Centre for Collaboration with Registry Networks is a specialized unit within Norway’s public health system that coordinates and advances the use of health registries for research, surveillance, and policy development.
  • C. Centre for Collaboration with Learning Health Systems Networks
    The Centre for Collaboration with Learning Health Systems Networks is a unit within the Norwegian Institute of Public Health that focuses on partnering with health system networks to continuously generate, share, and apply evidence for improving healthcare quality and outcomes.
  • D. Centre for Collaboration with Systems for Health Information Networks
    The Centre for Collaboration with Systems for Health Information Networks is a specialized unit within Norway’s public health sector that focuses on coordinating and improving digital health information systems and data sharing for public health purposes.
  • E. Jameel Clinic for Machine Learning in Health
    The Jameel Clinic for Machine Learning in Health is an MIT research center focused on applying artificial intelligence and machine learning to transform disease prevention, diagnosis, and treatment.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cross-Community Patient Discovery
Triple: [IHE XCPD, fullName, Cross-Community Patient Discovery]
Generated description
Cross-Community Patient Discovery is an IHE profile that enables healthcare organizations in different communities or domains to locate and match patient records across disparate health information systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cross-Community Patient Discovery
Target entity description: Cross-Community Patient Discovery is an IHE profile that enables healthcare organizations in different communities or domains to locate and match patient records across disparate health information systems.
  • A. Centre for Collaboration with Digital Health Networks
    The Centre for Collaboration with Digital Health Networks is a unit within the Norwegian Institute of Public Health that focuses on coordinating and advancing partnerships and initiatives in digital health.
  • B. Centre for Collaboration with Registry Networks
    The Centre for Collaboration with Registry Networks is a specialized unit within Norway’s public health system that coordinates and advances the use of health registries for research, surveillance, and policy development.
  • C. Centre for Collaboration with Learning Health Systems Networks
    The Centre for Collaboration with Learning Health Systems Networks is a unit within the Norwegian Institute of Public Health that focuses on partnering with health system networks to continuously generate, share, and apply evidence for improving healthcare quality and outcomes.
  • D. Centre for Collaboration with Systems for Health Information Networks
    The Centre for Collaboration with Systems for Health Information Networks is a specialized unit within Norway’s public health sector that focuses on coordinating and improving digital health information systems and data sharing for public health purposes.
  • E. Jameel Clinic for Machine Learning in Health
    The Jameel Clinic for Machine Learning in Health is an MIT research center focused on applying artificial intelligence and machine learning to transform disease prevention, diagnosis, and treatment.
  • F. None of above. chosen

Provenance (5 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe62a490481908ee0ad4ba9a94682 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e8399f481909992aedf0d918cbc completed April 2, 2026, 11:09 a.m.
NEDg Description generation batch_69ce4ffcf7488190b94cae18be14e8ff completed April 2, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69ce507766448190830dd3efc8a79a74 completed April 2, 2026, 11:18 a.m.
Created at: March 30, 2026, 6:16 p.m.