Triple
T29613956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ER universe |
E754807
|
entity |
| Predicate | hasFictionalHospitalType |
P46057
|
FINISHED |
| Object | public hospital |
—
|
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: public hospital | Statement: [ER universe, hasFictionalHospitalType, public hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalHospitalType Context triple: [ER universe, hasFictionalHospitalType, public hospital]
-
A.
fictionalHospital
chosen
Indicates that a hospital is imaginary or exists only within a fictional or narrative context, rather than in reality.
-
B.
hasHospitalType
Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
-
C.
hasFictionalClinic
Indicates that an entity is associated with or contains a clinic that exists only in a fictional or imaginary context.
-
D.
containsHospital
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
-
E.
isPublicHospital
Indicates that a hospital is owned, funded, or operated by a government or public authority rather than by private entities.
- 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_69f0ef85f62081909842b59fdf8717e1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69fdb31800508190beec15adb9bbd292 |
completed | May 8, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69fdb19c381c8190bafb2f565da097f1 |
completed | May 8, 2026, 9:49 a.m. |
Created at: April 28, 2026, 6:30 p.m.