Triple

T755104
Position Surface form Disambiguated ID Type / Status
Subject University Hospital Zurich E15535 entity
Predicate hasNotableDepartment P105 FINISHED
Object Department of Radiology
The Department of Radiology at University Hospital Zurich is a leading medical imaging center specializing in advanced diagnostic and interventional radiology for patient care, research, and education.
E88697 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: Department of Radiology | Statement: [University Hospital Zurich, hasNotableDepartment, Department of Radiology]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Radiology
Context triple: [University Hospital Zurich, hasNotableDepartment, Department of Radiology]
  • A. Department of Radiology
    The Department of Radiology at Cairo University's Faculty of Medicine is an academic and clinical unit specializing in medical imaging education, research, and diagnostic services.
  • B. Department of Radiology
    The Department of Radiology at University Medical Center Göttingen is a clinical and academic unit specializing in medical imaging for diagnosis, treatment planning, and research.
  • C. Department of Nuclear Medicine
    The Department of Nuclear Medicine is a clinical and research unit specializing in diagnostic imaging and radionuclide-based therapies using radioactive tracers and advanced imaging technologies.
  • D. Department of Radiology, Duke University
    The Department of Radiology at Duke University is a leading academic and clinical radiology center known for advanced imaging research, innovative diagnostic and interventional services, and comprehensive resident and fellowship training.
  • E. Department of Internal Medicine
    The Department of Internal Medicine at Cairo University's Faculty of Medicine is a major clinical and academic unit responsible for training physicians and providing specialized care across a wide range of adult medical subspecialties.
  • 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: Department of Radiology
Triple: [University Hospital Zurich, hasNotableDepartment, Department of Radiology]
Generated description
The Department of Radiology at University Hospital Zurich is a leading medical imaging center specializing in advanced diagnostic and interventional radiology for patient care, research, and education.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Radiology
Target entity description: The Department of Radiology at University Hospital Zurich is a leading medical imaging center specializing in advanced diagnostic and interventional radiology for patient care, research, and education.
  • A. Department of Radiology
    The Department of Radiology at Cairo University's Faculty of Medicine is an academic and clinical unit specializing in medical imaging education, research, and diagnostic services.
  • B. Department of Radiology
    The Department of Radiology at University Medical Center Göttingen is a clinical and academic unit specializing in medical imaging for diagnosis, treatment planning, and research.
  • C. Department of Nuclear Medicine
    The Department of Nuclear Medicine is a clinical and research unit specializing in diagnostic imaging and radionuclide-based therapies using radioactive tracers and advanced imaging technologies.
  • D. Department of Radiology, Duke University
    The Department of Radiology at Duke University is a leading academic and clinical radiology center known for advanced imaging research, innovative diagnostic and interventional services, and comprehensive resident and fellowship training.
  • E. Department of Internal Medicine
    The Department of Internal Medicine at Cairo University's Faculty of Medicine is a major clinical and academic unit responsible for training physicians and providing specialized care across a wide range of adult medical subspecialties.
  • 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a66820548190b373deb117187c2c completed March 1, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a654eae9608190af3b410ecc041660 completed March 3, 2026, 3:26 a.m.
NEDg Description generation batch_69a65555e7748190b2a55548e4058bc1 completed March 3, 2026, 3:28 a.m.
NED2 Entity disambiguation (via description) batch_69a656d5f28481908ff3fd5fb71b1440 completed March 3, 2026, 3:34 a.m.
Created at: March 1, 2026, 7:37 p.m.