Triple
T32451197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microdosing |
E829288
|
entity |
| Predicate | hasDoseCharacteristic |
P180074
|
FINISHED |
| Object | Sub-perceptual |
—
|
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: Sub-perceptual | Statement: [Microdosing, hasDoseCharacteristic, Sub-perceptual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDoseCharacteristic Context triple: [Microdosing, hasDoseCharacteristic, Sub-perceptual]
-
A.
hasDoseUnit
Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
-
B.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
C.
hasCommonDoseStrength
Indicates that two medicinal products share at least one identical dosage strength.
-
D.
hasDosingBasis
Indicates that one dosing specification is based on, derived from, or determined according to another dosing-related parameter or standard.
-
E.
hasDefinedDailyDose
Indicates that an entity has an established standard amount intended to be taken or used per day.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_69f730890a008190a882f7828f1c9162 |
completed | May 3, 2026, 11:24 a.m. |
Created at: May 1, 2026, 12:56 a.m.