Triple

T9685173
Position Surface form Disambiguated ID Type / Status
Subject Kyoto University Hospital E234387 entity
Predicate hasTypeOfPatients P35131 FINISHED
Object referral patients LITERAL 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: referral patients | Statement: [Kyoto University Hospital, hasTypeOfPatients, referral patients]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTypeOfPatients
Context triple: [Kyoto University Hospital, hasTypeOfPatients, referral patients]
  • A. hasPatient
    Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
  • B. hasPatientGroup chosen
    Indicates a relationship in which an entity (such as a study, treatment, or clinical activity) is associated with a specific group of patients it involves or targets.
  • C. hasHospitalType
    Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
  • D. primaryPatientType
    Indicates the main category or classification of patient that is primarily associated with or targeted by an entity, action, or service.
  • E. healthcareType
    Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
  • F. None of above.

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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9cd0877c81909fde1989d946aae9 completed April 1, 2026, 10:31 p.m.
PD Predicate disambiguation batch_69ccd5b840f081909f66bf0b66d17d9b completed April 1, 2026, 8:22 a.m.
Created at: March 30, 2026, 8:16 p.m.