Triple
T15959454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County General Hospital |
E387018
|
entity |
| Predicate | departmentFeatured |
P1467
|
FINISHED |
| Object | emergency department |
—
|
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: emergency department | Statement: [County General Hospital, departmentFeatured, emergency department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departmentFeatured Context triple: [County General Hospital, departmentFeatured, emergency department]
-
A.
department
chosen
Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
-
B.
featuredArea
Indicates that an area or section is highlighted or given special prominence within a larger context or layout.
-
C.
workFeatured
Indicates that one work is highlighted, showcased, or given special prominence within a particular context, collection, or presentation.
-
D.
alsoFeatured
Indicates that an entity appears in addition to another primary entity within the same context, work, or presentation.
-
E.
featuredFor
Indicates that one entity is highlighted, promoted, or specially showcased in the context or for the benefit of 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:53 a.m.