Triple
T33206241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebastine |
E850018
|
entity |
| Predicate | hasStandardDose |
P37218
|
FINISHED |
| Object | 10 mg once daily for allergic rhinitis in adults |
—
|
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 mg once daily for allergic rhinitis in adults | Statement: [Ebastine, hasStandardDose, 10 mg once daily for allergic rhinitis in adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardDose Context triple: [Ebastine, hasStandardDose, 10 mg once daily for allergic rhinitis in adults]
-
A.
hasDoseUnit
Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
-
B.
hasCommonStartingDose_mgPerDay
Indicates that two treatments share the same typical initial dosage, measured in milligrams per day.
-
C.
hasHigherDoseStrength
Indicates that one entity has a greater dose strength than another entity in a comparative relationship.
-
D.
typicalDoseCount
Indicates the usual number of doses administered or taken in a standard course of use.
-
E.
hasDosingRegimen
chosen
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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff397e19a88190a945b826159f5290 |
completed | May 9, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69ff392400d0819088d30d08d4a774bd |
completed | May 9, 2026, 1:39 p.m. |
Created at: May 1, 2026, 1:30 a.m.