Triple
T23186545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mectizan |
E579606
|
entity |
| Predicate | hasFormulationStrength |
P151277
|
FINISHED |
| Object | 3 mg tablet |
—
|
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: 3 mg tablet | Statement: [Mectizan, hasFormulationStrength, 3 mg tablet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormulationStrength Context triple: [Mectizan, hasFormulationStrength, 3 mg tablet]
-
A.
hasFormulation
Indicates that one entity is expressed, prepared, or configured in a particular form or composition defined by another entity.
-
B.
hasHigherDoseStrength
Indicates that one entity has a greater dose strength than another entity in a comparative relationship.
-
C.
isFormulatedUsing
Indicates that something is created, defined, or expressed by means of a specified method, material, or set of components.
-
D.
hasFormulationType
Indicates the specific way something is physically prepared or presented, such as its dosage form, composition, or delivery format.
-
E.
exampleFormulation
Indicates that one entity serves as a representative or illustrative formulation or expression of another entity.
- F. None of above. chosen
Provenance (4 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fd3aaa08190b9cf7afe4ee5a38d |
completed | April 29, 2026, 4:57 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b75e2708190ba48875e36f983bc |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4:05 p.m.