Triple
T16952516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daypro |
E411217
|
entity |
| Predicate | mayIncreaseRiskOf |
P12716
|
FINISHED |
| Object | cardiovascular thrombotic events |
—
|
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: cardiovascular thrombotic events | Statement: [Daypro, mayIncreaseRiskOf, cardiovascular thrombotic events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayIncreaseRiskOf Context triple: [Daypro, mayIncreaseRiskOf, cardiovascular thrombotic events]
-
A.
mayResultIn
chosen
Indicates that one entity has the potential to cause, lead to, or bring about another entity or outcome, without guaranteeing that it will occur.
-
B.
riskReductionFor
Indicates a relationship where one entity decreases or mitigates the level of risk associated with another entity or situation.
-
C.
riskElement
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
D.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
-
E.
riskFactorForInfection
Indicates that something increases the likelihood or susceptibility of an entity to develop a particular infection.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0197f308190af7185fc9cc7a6e9 |
completed | April 18, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.