Triple
T37706599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nurofen |
E939212
|
entity |
| Predicate | typicalAdultDoseMg |
P204350
|
FINISHED |
| Object | 200 |
—
|
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: 200 | Statement: [Nurofen, typicalAdultDoseMg, 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAdultDoseMg Context triple: [Nurofen, typicalAdultDoseMg, 200]
-
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.
hasInitialAdultDose
Indicates the standard amount of a medication that should be given to an adult patient for the first dose.
-
D.
dosageLevel
Indicates the specific amount or intensity of a substance or treatment administered in a given dose.
-
E.
typicalDosingFrequency
Indicates how often a treatment or medication is usually administered within a standard dosing regimen.
- F. None of above. chosen
Provenance (4 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_69f76edb49dc8190b951dce9ce6ef789 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:18 p.m.