Triple
T6251263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merck Mectizan Donation Program |
E140050
|
entity |
| Predicate | supportsInterventionType |
P41951
|
FINISHED |
| Object | mass drug administration |
—
|
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: mass drug administration | Statement: [Merck Mectizan Donation Program, supportsInterventionType, mass drug administration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsInterventionType Context triple: [Merck Mectizan Donation Program, supportsInterventionType, mass drug administration]
-
A.
interventionType
chosen
Indicates the specific kind or category of action, treatment, or measure applied in an intervention.
-
B.
supportsType
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
C.
supportsTreatmentType
Indicates that one entity is capable of providing, handling, or is compatible with a specified type of treatment.
-
D.
supportsMissionType
Indicates that one entity is capable of handling, enabling, or being compatible with a specified type of mission.
-
E.
supportsProgramType
Indicates that one entity is capable of handling, offering, or being compatible with a specified type of program.
- 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.