Triple
T9833895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | diphtheria antitoxin |
E239052
|
entity |
| Predicate | regimenDependsOn |
P90239
|
FINISHED |
| Object | severity of disease |
—
|
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: severity of disease | Statement: [diphtheria antitoxin, regimenDependsOn, severity of disease]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regimenDependsOn Context triple: [diphtheria antitoxin, regimenDependsOn, severity of disease]
-
A.
doseRegimen
Indicates the specific schedule, frequency, and amount with which a dose of a substance or medication is to be administered.
-
B.
belongsToRegimen
Indicates that something is a component or member of a specified regimen or structured treatment plan.
-
C.
hasDosingRegimen
Indicates that an entity is associated with a specific dosing regimen, defining how and when a dose is to be administered.
-
D.
belongsToRegimenType
Indicates that something is associated with or classified under a specific regimen type.
-
E.
hasLoadingDoseRegimen
Indicates that an entity is associated with a specific initial (loading) dosing regimen administered to rapidly achieve a desired therapeutic level.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3385054819094145c96204e3f0d |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:32 p.m.