Triple
T19772784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lipitor |
E474929
|
entity |
| Predicate | typicalDoseRange |
P14599
|
FINISHED |
| Object | 10–80 mg once daily |
—
|
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: 10–80 mg once daily | Statement: [Lipitor, typicalDoseRange, 10–80 mg once daily]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDoseRange Context triple: [Lipitor, typicalDoseRange, 10–80 mg once daily]
-
A.
typicalDosageCategories
chosen
Indicates the standard dosage ranges or categories typically associated with a given treatment, substance, or medication.
-
B.
typicalDosingFrequency
Indicates how often a treatment or medication is usually administered within a standard dosing regimen.
-
C.
maximumDailyDoseTypicalAdult
Indicates the highest amount of a substance that a typical adult is recommended or allowed to take in one day.
-
D.
typicalDosageStyles
Indicates the usual ways or patterns in which a dosage is administered or presented (e.g., standard amounts, frequencies, or formats).
-
E.
dosageLevel
Indicates the specific amount or intensity of a substance or treatment administered in a given dose.
- 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_69e6535ce4d08190a1dfca2df95a8631 |
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.