Triple
T5946192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Medicine & Dentistry |
E132285
|
entity |
| Predicate | hasDivision |
P35
|
FINISHED |
| Object |
Department of Radiology & Diagnostic Imaging
The Department of Radiology & Diagnostic Imaging is an academic medical department specializing in imaging-based diagnosis, clinical services, and training within the Faculty of Medicine & Dentistry.
|
E556708
|
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 & Diagnostic Imaging | Statement: [Faculty of Medicine & Dentistry, hasDivision, Department of Radiology & Diagnostic Imaging]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Radiology & Diagnostic Imaging Context triple: [Faculty of Medicine & Dentistry, hasDivision, Department of Radiology & Diagnostic Imaging]
-
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 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.
-
D.
Department of Radiology
The Department of Radiology at the University of Tokyo’s Faculty of Medicine is a leading academic and clinical center specializing in medical imaging, image-guided diagnosis, and interventional radiology.
-
E.
Department of Radiology
The Department of Radiology at Tohoku University's Faculty of Medicine is an academic and clinical unit specializing in medical imaging, image-guided diagnosis, and radiological research and education.
- 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 & Diagnostic Imaging Triple: [Faculty of Medicine & Dentistry, hasDivision, Department of Radiology & Diagnostic Imaging]
Generated description
The Department of Radiology & Diagnostic Imaging is an academic medical department specializing in imaging-based diagnosis, clinical services, and training within the Faculty of Medicine & Dentistry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Radiology & Diagnostic Imaging Target entity description: The Department of Radiology & Diagnostic Imaging is an academic medical department specializing in imaging-based diagnosis, clinical services, and training within the Faculty of Medicine & Dentistry.
-
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 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.
-
D.
Department of Radiology
The Department of Radiology at the University of Tokyo’s Faculty of Medicine is a leading academic and clinical center specializing in medical imaging, image-guided diagnosis, and interventional radiology.
-
E.
Department of Radiology
The Department of Radiology at Tohoku University's Faculty of Medicine is an academic and clinical unit specializing in medical imaging, image-guided diagnosis, and radiological research and education.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0393bd4488190bba68d9c6e872e04 |
completed | March 22, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c08a11f48190b16ca30842f23ce5 |
completed | March 23, 2026, 4:24 a.m. |
| NEDg | Description generation | batch_69c0c351dcf88190a21b9c782cc06809 |
completed | March 23, 2026, 4:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0c3e09a288190a230dd40d94dc7ba |
completed | March 23, 2026, 4:38 a.m. |
Created at: March 22, 2026, 4:01 p.m.