Triple
T6251145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Decision to provide ivermectin (Mectizan) free of charge for river blindness |
E140047
|
entity |
| Predicate | hasTreatmentFrequency |
P37218
|
FINISHED |
| Object | annual treatment |
—
|
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: annual treatment | Statement: [Decision to provide ivermectin (Mectizan) free of charge for river blindness, hasTreatmentFrequency, annual treatment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTreatmentFrequency Context triple: [Decision to provide ivermectin (Mectizan) free of charge for river blindness, hasTreatmentFrequency, annual treatment]
-
A.
hasDosingRegimen
chosen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
B.
hasSubsequentTreatment
Indicates that one treatment occurs after and in continuation of another treatment in a temporal sequence.
-
C.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
-
D.
hasDefinedDailyDose
Indicates that an entity has an established standard amount intended to be taken or used per day.
-
E.
hasCommunicationFrequency
Indicates how often communication occurs between the related entities.
- 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.