Triple
T97374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of Clinical Medicine, University of Cambridge |
E1961
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Anaesthesia, University of Cambridge
The Department of Anaesthesia at the University of Cambridge is a leading academic and clinical centre focused on research, education, and training in anaesthesia, perioperative medicine, and pain management.
|
E15804
|
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 Anaesthesia, University of Cambridge | Statement: [School of Clinical Medicine, University of Cambridge, hasDepartment, Department of Anaesthesia, University of Cambridge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Anaesthesia, University of Cambridge Context triple: [School of Clinical Medicine, University of Cambridge, hasDepartment, Department of Anaesthesia, University of Cambridge]
-
A.
Department of Medicine, University of Cambridge
The Department of Medicine at the University of Cambridge is a major academic and clinical research department focused on advancing medical science and training healthcare professionals within the university’s School of Clinical Medicine.
-
B.
Department of Surgery, University of Cambridge
The Department of Surgery at the University of Cambridge is an academic and clinical department specializing in surgical research, education, and training within the university’s School of Clinical Medicine.
-
C.
School of Clinical Medicine, University of Cambridge
The School of Clinical Medicine at the University of Cambridge is the institution’s primary center for medical education, clinical training, and biomedical research.
-
D.
Department of Obstetrics and Gynaecology, University of Cambridge
The Department of Obstetrics and Gynaecology at the University of Cambridge is an academic and clinical centre focused on research, education, and specialist care in pregnancy, childbirth, and women's reproductive health.
-
E.
Department of Paediatrics, University of Cambridge
The Department of Paediatrics at the University of Cambridge is a leading academic and clinical centre focused on research, education, and training in child health and pediatric medicine.
- 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 Anaesthesia, University of Cambridge Triple: [School of Clinical Medicine, University of Cambridge, hasDepartment, Department of Anaesthesia, University of Cambridge]
Generated description
The Department of Anaesthesia at the University of Cambridge is a leading academic and clinical centre focused on research, education, and training in anaesthesia, perioperative medicine, and pain management.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Anaesthesia, University of Cambridge Target entity description: The Department of Anaesthesia at the University of Cambridge is a leading academic and clinical centre focused on research, education, and training in anaesthesia, perioperative medicine, and pain management.
-
A.
Department of Medicine, University of Cambridge
The Department of Medicine at the University of Cambridge is a major academic and clinical research department focused on advancing medical science and training healthcare professionals within the university’s School of Clinical Medicine.
-
B.
Department of Surgery, University of Cambridge
The Department of Surgery at the University of Cambridge is an academic and clinical department specializing in surgical research, education, and training within the university’s School of Clinical Medicine.
-
C.
School of Clinical Medicine, University of Cambridge
The School of Clinical Medicine at the University of Cambridge is the institution’s primary center for medical education, clinical training, and biomedical research.
-
D.
Department of Obstetrics and Gynaecology, University of Cambridge
The Department of Obstetrics and Gynaecology at the University of Cambridge is an academic and clinical centre focused on research, education, and specialist care in pregnancy, childbirth, and women's reproductive health.
-
E.
Department of Paediatrics, University of Cambridge
The Department of Paediatrics at the University of Cambridge is a leading academic and clinical centre focused on research, education, and training in child health and pediatric medicine.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2b014ab2c8190bcef8382280932dc |
completed | Feb. 28, 2026, 9:06 a.m. |
| NEDg | Description generation | batch_69a2b0bd233c81908f3595abdfa51666 |
completed | Feb. 28, 2026, 9:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2b122a168819088be9e5455a1aac1 |
completed | Feb. 28, 2026, 9:10 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.