Triple
T755091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Hospital Zurich |
E15535
|
entity |
| Predicate | hasBedCapacityApprox |
P17054
|
FINISHED |
| Object | 900 |
—
|
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: 900 | Statement: [University Hospital Zurich, hasBedCapacityApprox, 900]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBedCapacityApprox Context triple: [University Hospital Zurich, hasBedCapacityApprox, 900]
-
A.
beds
chosen
Indicates that one entity provides or designates a place for another entity to sleep or rest.
-
B.
numberOfBedrooms
Indicates the quantity of bedrooms associated with a given property or dwelling.
-
C.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
D.
numberOfBathrooms
Indicates the total count of bathrooms associated with an entity (such as a property or unit).
-
E.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.