Triple
T22692763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5q13 (SMN1) |
E561092
|
entity |
| Predicate | isDosageSensitive |
P149312
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [5q13 (SMN1), isDosageSensitive, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDosageSensitive Context triple: [5q13 (SMN1), isDosageSensitive, true]
-
A.
dosageLevel
Indicates the specific amount or intensity of a substance or treatment administered in a given dose.
-
B.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
C.
dosageStyle
Indicates the manner or pattern in which a dose of a substance (such as a medication) is administered or taken.
-
D.
hasDoseUnit
Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
-
E.
hasDosageForm
Indicates the specific physical form or presentation in which a drug or medicinal product is supplied or administered (e.g., tablet, injection, cream).
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789ba0148190891781d05ec64f3c |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:13 p.m.