Triple
T6005207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waylivra |
E133691
|
entity |
| Predicate | initialDosingRegimen |
P37218
|
FINISHED |
| Object | more frequent injections during loading phase |
—
|
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: more frequent injections during loading phase | Statement: [Waylivra, initialDosingRegimen, more frequent injections during loading phase]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialDosingRegimen Context triple: [Waylivra, initialDosingRegimen, more frequent injections during loading phase]
-
A.
doseRegimen
Indicates the specific schedule, frequency, and amount with which a dose of a substance or medication is to be administered.
-
B.
hasDosingRegimen
chosen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
C.
hasMaintenanceDose
Indicates that an entity is associated with a specific ongoing dose used to maintain a desired therapeutic effect after initial treatment.
-
D.
hasInitialDose
Indicates that an entity has received or is assigned a first or starting dose of a treatment, medication, or substance.
-
E.
dosingInterval
Indicates the time period that should elapse between consecutive doses of a medication or treatment.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f10d18081908c351170b7f58d3d |
completed | March 22, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:06 p.m.