Triple
T16006556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free Hospital for the Treatment of Smallpox and other Diseases of the Skin |
E388234
|
entity |
| Predicate | treatsDisease |
P88196
|
FINISHED |
| Object | smallpox |
—
|
LITERAL 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: smallpox | Statement: [Free Hospital for the Treatment of Smallpox and other Diseases of the Skin, treatsDisease, smallpox]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsDisease Context triple: [Free Hospital for the Treatment of Smallpox and other Diseases of the Skin, treatsDisease, smallpox]
-
A.
knownForTreatmentOf
chosen
Indicates that an entity is recognized or notable for providing treatment or medical care for a particular condition, disease, or type of patient.
-
B.
hasTargetDisease
Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
-
C.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
D.
targetsDiseaseVector
Indicates that an entity is directed at, designed to affect, or intended to control a particular disease-carrying vector organism.
-
E.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
- F. None of above.
Provenance (3 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142dc081c819082527e3fa8773460 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:55 a.m.