Triple
T27657173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Infectious Diseases, Johns Hopkins University |
E697024
|
entity |
| Predicate | collaboratesWith |
P37
|
FINISHED |
| Object |
Johns Hopkins Bloomberg School of Public Health Department of Epidemiology
The Johns Hopkins Bloomberg School of Public Health Department of Epidemiology is a leading academic department focused on researching the distribution and determinants of diseases in populations and training public health professionals in epidemiologic methods.
|
E1782939
|
NE FINISHED |
How this triple was built (2 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: Johns Hopkins Bloomberg School of Public Health Department of Epidemiology | Statement: [Division of Infectious Diseases, Johns Hopkins University, collaboratesWith, Johns Hopkins Bloomberg School of Public Health Department of Epidemiology]
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: Johns Hopkins Bloomberg School of Public Health Department of Epidemiology Triple: [Division of Infectious Diseases, Johns Hopkins University, collaboratesWith, Johns Hopkins Bloomberg School of Public Health Department of Epidemiology]
Generated description
The Johns Hopkins Bloomberg School of Public Health Department of Epidemiology is a leading academic department focused on researching the distribution and determinants of diseases in populations and training public health professionals in epidemiologic methods.
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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f631d9b078819088c275581681825e |
completed | May 2, 2026, 5:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12da9c5f3881909282cfb27a2c4624 |
completed | May 24, 2026, 11:01 a.m. |
| NEDg | Description generation | batch_6a12dba401e081909133c45b038798e5 |
completed | May 24, 2026, 11:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a12dc0d6f8881908c158355b595139c |
completed | May 24, 2026, 11:07 a.m. |
Created at: April 27, 2026, 2:34 p.m.