Triple
T11115474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motrin |
E262873
|
entity |
| Predicate | hasOverdoseRisk |
P76077
|
FINISHED |
| Object | kidney damage |
—
|
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: kidney damage | Statement: [Motrin, hasOverdoseRisk, kidney damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOverdoseRisk Context triple: [Motrin, hasOverdoseRisk, kidney damage]
-
A.
riskOfOverdose
chosen
Indicates a likelihood or potential that the subject will experience a drug or substance overdose, given certain conditions or factors.
-
B.
hasAddictionPotential
Indicates that one entity (typically a substance or activity) has the capacity to cause another entity (typically a person) to develop dependence or addictive behavior toward it.
-
C.
hasAddictiveSubstance
Indicates that an entity contains or involves a substance capable of causing addiction in those who use or consume it.
-
D.
associatedWithSubstance
Indicates that one entity has a relevant connection or involvement with a particular substance, such as use, presence, exposure, or composition.
-
E.
hasNotableDrug
Indicates that an entity is associated with a drug that is considered notable or significant in some recognized context.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79aa7254c8190abce35696ad2be03 |
completed | April 9, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69d7441cf8188190b8095f622c923156 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.