Triple
T19773685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Synagis |
E474951
|
entity |
| Predicate | hasDosage |
P130936
|
FINISHED |
| Object | 15 mg/kg once monthly |
—
|
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: 15 mg/kg once monthly | Statement: [Synagis, hasDosage, 15 mg/kg once monthly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDosage Context triple: [Synagis, hasDosage, 15 mg/kg once monthly]
-
A.
hasDoseUnit
Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
-
B.
hasDosageForm
Indicates the specific physical form or presentation in which a drug or medicinal product is supplied or administered (e.g., tablet, injection, cream).
-
C.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
D.
dosageLevel
chosen
Indicates the specific amount or intensity of a substance or treatment administered in a given dose.
-
E.
hasDefinedDailyDose
Indicates that an entity has an established standard amount intended to be taken or used per day.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535e450c8190a2628245ae0d0bd3 |
completed | April 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.