Triple
T6251281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merck Mectizan Donation Program |
E140050
|
entity |
| Predicate | addressesHealthIssue |
P3847
|
FINISHED |
| Object | blindness prevention |
—
|
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: blindness prevention | Statement: [Merck Mectizan Donation Program, addressesHealthIssue, blindness prevention]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressesHealthIssue Context triple: [Merck Mectizan Donation Program, addressesHealthIssue, blindness prevention]
-
A.
addressesIssue
chosen
Indicates that one entity deals with, responds to, or attempts to resolve a specific issue associated with another entity.
-
B.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
C.
positionOnHealthCare
Indicates a person or entity’s stance, opinion, or policy preference regarding health care systems, services, or reforms.
-
D.
medicalCar
Indicates that an entity is a vehicle used for providing medical transport or emergency medical services to another entity.
-
E.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
- 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_69c008b4858c819095b0199114a9a87b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633fb2ac8190b71b8e35fa923300 |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:24 p.m.