Triple
T36599492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tucatinib |
E902879
|
entity |
| Predicate | hasUsualAdultDose |
P130936
|
FINISHED |
| Object | 300 mg twice 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: 300 mg twice daily | Statement: [tucatinib, hasUsualAdultDose, 300 mg twice daily]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUsualAdultDose Context triple: [tucatinib, hasUsualAdultDose, 300 mg twice daily]
-
A.
maximumDailyDoseTypicalAdult
Indicates the highest amount of a substance that a typical adult is recommended or allowed to take in one day.
-
B.
typicalDoseCount
Indicates the usual number of doses administered or taken in a standard course of use.
-
C.
hasDoseUnit
Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
-
D.
hasDefinedDailyDose
Indicates that an entity has an established standard amount intended to be taken or used per day.
-
E.
dosageLevel
chosen
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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.