Triple
T11996876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yusuf |
E285553
|
entity |
| Predicate | riskInWork |
P62537
|
FINISHED |
| Object | use of extremely strong sedatives that complicate waking |
—
|
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: use of extremely strong sedatives that complicate waking | Statement: [Yusuf, riskInWork, use of extremely strong sedatives that complicate waking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskInWork Context triple: [Yusuf, riskInWork, use of extremely strong sedatives that complicate waking]
-
A.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
-
B.
riskElement
chosen
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
C.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
D.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
E.
risk
Indicates that one entity is exposed or subject to potential harm, loss, or adverse outcome arising from another entity, action, or situation.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.