Triple
T27660043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skyrizi |
E697097
|
entity |
| Predicate | dosingForm |
P23152
|
FINISHED |
| Object | prefilled syringe |
—
|
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: prefilled syringe | Statement: [Skyrizi, dosingForm, prefilled syringe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dosingForm Context triple: [Skyrizi, dosingForm, prefilled syringe]
-
A.
hasDosageForm
chosen
Indicates the specific physical form or presentation in which a drug or medicinal product is supplied or administered (e.g., tablet, injection, cream).
-
B.
dosageStyles
Indicates the various ways or formats in which a dosage (amount and schedule of administration) is specified or presented for a treatment or medication.
-
C.
dosageStyle
Indicates the manner or pattern in which a dose of a substance (such as a medication) is administered or taken.
-
D.
hasDoseUnit
Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
-
E.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
- 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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f634a016b08190973fd3a552a9757c |
completed | May 2, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69f62c1a92648190835a2c5250d8c758 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:36 p.m.