Triple
T8541376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Kabete Campus |
E202203
|
entity |
| Predicate | hostsDepartment |
P3556
|
FINISHED |
| Object |
Department of Public Health, Pharmacology and Toxicology, University of Nairobi
The Department of Public Health, Pharmacology and Toxicology at the University of Nairobi is an academic and research unit focused on public health, drug action, and toxic substances, particularly in veterinary and related biomedical fields.
|
E741150
|
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 Public Health, Pharmacology and Toxicology, University of Nairobi | Statement: [Upper Kabete Campus, hostsDepartment, Department of Public Health, Pharmacology and Toxicology, University of Nairobi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Public Health, Pharmacology and Toxicology, University of Nairobi Context triple: [Upper Kabete Campus, hostsDepartment, Department of Public Health, Pharmacology and Toxicology, University of Nairobi]
-
A.
Department of Pharmacology and Toxicology (University of Utah)
The Department of Pharmacology and Toxicology at the University of Utah is an academic unit focused on research and education in drug action, safety, and the biological mechanisms underlying therapeutic and toxic effects.
-
B.
Department of Public Health Sciences
The Department of Public Health Sciences is an academic unit focused on research and education in population health, epidemiology, and health policy within the School of Medicine and Dentistry.
-
C.
School of Health Systems and Public Health, University of Pretoria
The School of Health Systems and Public Health at the University of Pretoria is an academic and research institution focused on training professionals and generating evidence to improve public health and health systems in South Africa and beyond.
-
D.
Department of Public Health, Kyoto University
The Department of Public Health at Kyoto University is an academic and research unit specializing in population health, epidemiology, and preventive medicine within the university’s Faculty of Medicine.
-
E.
Faculty of Public Health
The Faculty of Public Health is an academic unit of Al-Quds University dedicated to education and research in public health and related disciplines.
- 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 Public Health, Pharmacology and Toxicology, University of Nairobi Triple: [Upper Kabete Campus, hostsDepartment, Department of Public Health, Pharmacology and Toxicology, University of Nairobi]
Generated description
The Department of Public Health, Pharmacology and Toxicology at the University of Nairobi is an academic and research unit focused on public health, drug action, and toxic substances, particularly in veterinary and related biomedical fields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Public Health, Pharmacology and Toxicology, University of Nairobi Target entity description: The Department of Public Health, Pharmacology and Toxicology at the University of Nairobi is an academic and research unit focused on public health, drug action, and toxic substances, particularly in veterinary and related biomedical fields.
-
A.
Department of Pharmacology and Toxicology (University of Utah)
The Department of Pharmacology and Toxicology at the University of Utah is an academic unit focused on research and education in drug action, safety, and the biological mechanisms underlying therapeutic and toxic effects.
-
B.
Department of Public Health Sciences
The Department of Public Health Sciences is an academic unit focused on research and education in population health, epidemiology, and health policy within the School of Medicine and Dentistry.
-
C.
School of Health Systems and Public Health, University of Pretoria
The School of Health Systems and Public Health at the University of Pretoria is an academic and research institution focused on training professionals and generating evidence to improve public health and health systems in South Africa and beyond.
-
D.
Department of Public Health, Kyoto University
The Department of Public Health at Kyoto University is an academic and research unit specializing in population health, epidemiology, and preventive medicine within the university’s Faculty of Medicine.
-
E.
Faculty of Public Health
The Faculty of Public Health at the University of Indonesia is an academic unit dedicated to education and research in public health, preparing professionals to address population health challenges and promote community well-being.
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc4578d9c8819096b3853d01c3ec11 |
completed | March 31, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6da3d65c819087ed6b46dfc35885 |
completed | April 2, 2026, 1:22 p.m. |
| NEDg | Description generation | batch_69ce6ec3b080819082d64646d453541d |
completed | April 2, 2026, 1:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce6fe928d48190824e7a94fea5cfc0 |
completed | April 2, 2026, 1:32 p.m. |
Created at: March 30, 2026, 6:18 p.m.