Triple
T7101620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Institute of Public Health (Charité) |
E165471
|
entity |
| Predicate | hasUnit |
P35
|
FINISHED |
| Object |
Department of Epidemiology and Biostatistics
The Department of Epidemiology and Biostatistics is an academic unit specializing in the study of disease patterns, health determinants, and the statistical methods used to analyze public health and medical data.
|
E641629
|
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 Epidemiology and Biostatistics | Statement: [Institute of Public Health (Charité), hasUnit, Department of Epidemiology and Biostatistics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology and Biostatistics Context triple: [Institute of Public Health (Charité), hasUnit, Department of Epidemiology and Biostatistics]
-
A.
Department of Epidemiology, Biostatistics and Occupational Health
The Department of Epidemiology, Biostatistics and Occupational Health is an academic unit at McGill University specializing in research and graduate education on population health, statistical methods, and workplace health risks.
-
B.
Department of Biostatistics
The Department of Biostatistics at the Harvard T.H. Chan School of Public Health is a leading academic center for developing and applying statistical methods to advance biomedical, public health, and quantitative science research.
-
C.
Department of Epidemiology, Harvard T.H. Chan School of Public Health
The Department of Epidemiology at the Harvard T.H. Chan School of Public Health is a leading academic and research department focused on studying the distribution, determinants, and prevention of disease in populations worldwide.
-
D.
School of Epidemiology and Public Health
The School of Epidemiology and Public Health is an academic unit at the University of Ottawa dedicated to research and graduate education in epidemiology, biostatistics, and public health.
-
E.
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.
- 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 Epidemiology and Biostatistics Triple: [Institute of Public Health (Charité), hasUnit, Department of Epidemiology and Biostatistics]
Generated description
The Department of Epidemiology and Biostatistics is an academic unit specializing in the study of disease patterns, health determinants, and the statistical methods used to analyze public health and medical data.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology and Biostatistics Target entity description: The Department of Epidemiology and Biostatistics is an academic unit specializing in the study of disease patterns, health determinants, and the statistical methods used to analyze public health and medical data.
-
A.
Department of Epidemiology, Biostatistics and Occupational Health
The Department of Epidemiology, Biostatistics and Occupational Health is an academic unit at McGill University specializing in research and graduate education on population health, statistical methods, and workplace health risks.
-
B.
Department of Biostatistics
The Department of Biostatistics at the Harvard T.H. Chan School of Public Health is a leading academic center for developing and applying statistical methods to advance biomedical, public health, and quantitative science research.
-
C.
Department of Epidemiology, Harvard T.H. Chan School of Public Health
The Department of Epidemiology at the Harvard T.H. Chan School of Public Health is a leading academic and research department focused on studying the distribution, determinants, and prevention of disease in populations worldwide.
-
D.
School of Epidemiology and Public Health
The School of Epidemiology and Public Health is an academic unit at the University of Ottawa dedicated to research and graduate education in epidemiology, biostatistics, and public health.
-
E.
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.
- 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_69c6887fcddc8190a5d58908f6dee590 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e588aee08190bfb3d96135c0a322 |
completed | March 27, 2026, 8:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79ca9b58c8190a91023de6811b21a |
completed | March 28, 2026, 9:17 a.m. |
| NEDg | Description generation | batch_69c79d16d3408190a36ab53d5d202e15 |
completed | March 28, 2026, 9:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79dc7d7d8819097e423ef70b03040 |
completed | March 28, 2026, 9:22 a.m. |
Created at: March 27, 2026, 2:42 p.m.