Triple
T24825315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opening Eyes |
E621170
|
entity |
| Predicate | typeOfScreening |
P9177
|
FINISHED |
| Object | preventive health screening |
—
|
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: preventive health screening | Statement: [Opening Eyes, typeOfScreening, preventive health screening]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfScreening Context triple: [Opening Eyes, typeOfScreening, preventive health screening]
-
A.
screeningType
chosen
Indicates the specific method or category of screening applied in a screening process or evaluation.
-
B.
screeningOutcome
Indicates the result or decision produced by a screening or evaluation process applied to an entity.
-
C.
screeningBasis
Indicates the underlying reason, criterion, or grounds on which a screening or evaluation is conducted between entities.
-
D.
screenedWith
Indicates that one entity is examined, tested, or evaluated using another entity as the screening method, tool, or criterion.
-
E.
hasScreening
Indicates that one entity conducts, hosts, or is associated with a particular screening event involving another entity.
- 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_69e2fac0c3b881909110e5a56c6fa46f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 18, 2026, 5:05 a.m.