Triple
T5906664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hal Morgenstern |
E131356
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object |
Department of Epidemiology, University of Michigan School of Public Health
The Department of Epidemiology at the University of Michigan School of Public Health is a leading academic and research unit focused on studying the distribution, determinants, and prevention of disease in populations.
|
E553218
|
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, University of Michigan School of Public Health | Statement: [Hal Morgenstern, memberOf, Department of Epidemiology, University of Michigan School of Public Health]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology, University of Michigan School of Public Health Context triple: [Hal Morgenstern, memberOf, Department of Epidemiology, University of Michigan School of Public Health]
-
A.
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.
-
B.
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.
-
C.
School of Public Health
The School of Public Health at the University of Minnesota is an academic institution dedicated to education, research, and community engagement in public health and population health sciences.
-
D.
School of Public Health
The School of Public Health at West Virginia University is an academic unit dedicated to education, research, and community engagement in public health disciplines.
-
E.
School of Public Health
The School of Public Health at Sun Yat-sen University is an academic institution dedicated to education and research in public health, preventive medicine, and related health sciences.
- 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, University of Michigan School of Public Health Triple: [Hal Morgenstern, memberOf, Department of Epidemiology, University of Michigan School of Public Health]
Generated description
The Department of Epidemiology at the University of Michigan School of Public Health is a leading academic and research unit focused on studying the distribution, determinants, and prevention of disease in populations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Epidemiology, University of Michigan School of Public Health Target entity description: The Department of Epidemiology at the University of Michigan School of Public Health is a leading academic and research unit focused on studying the distribution, determinants, and prevention of disease in populations.
-
A.
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.
-
B.
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.
-
C.
School of Public Health
The School of Public Health at the University of Minnesota is an academic institution dedicated to education, research, and community engagement in public health and population health sciences.
-
D.
School of Public Health
The School of Public Health at Sun Yat-sen University is an academic institution dedicated to education and research in public health, preventive medicine, and related health sciences.
-
E.
School of Public Health
The School of Public Health at West Virginia University is an academic unit dedicated to education, research, and community engagement in public health disciplines.
- 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_69c0085864a88190a569c05ff7d65f29 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03772d9dc8190899fe49ef887e685 |
completed | March 22, 2026, 6:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b16ba6c881908e9a909bf86ea92d |
completed | March 23, 2026, 3:20 a.m. |
| NEDg | Description generation | batch_69c0b2751c2081908c8d47c9c0c26e84 |
completed | March 23, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0b2d6d5688190936858046377d192 |
completed | March 23, 2026, 3:26 a.m. |
Created at: March 22, 2026, 3:59 p.m.