Triple
T34186144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenelle Evans |
E876964
|
entity |
| Predicate | hasNotableHealthIssue |
—
|
GENERATED |
| Object | publicly discussed mental health struggles |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableHealthIssue Context triple: [Jenelle Evans, hasNotableHealthIssue, publicly discussed mental health struggles]
-
A.
hasHealthConcern
chosen
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
B.
hasHealthCode
Indicates that an entity is associated with a specific health-related classification or status code.
-
C.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
D.
hasHealthCareCharacteristic
Indicates that an entity possesses a specific healthcare-related attribute, quality, or feature.
-
E.
hasNoIssue
Indicates that there are no problems, defects, or conflicts associated with the referenced entity or situation.
- F. None of above.
Provenance (1 batch)
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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 1:55 a.m.