Triple
T17717172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Manchester General Hospital |
E442228
|
entity |
| Predicate | bedCountApproximate |
P29715
|
FINISHED |
| Object | 600+ |
—
|
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: 600+ | Statement: [North Manchester General Hospital, bedCountApproximate, 600+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bedCountApproximate Context triple: [North Manchester General Hospital, bedCountApproximate, 600+]
-
A.
bedCount
chosen
Indicates the number of beds associated with an entity, such as a room, facility, or accommodation.
-
B.
numberOfBedrooms
Indicates the quantity of bedrooms associated with a given property or dwelling.
-
C.
approximateNumberOfRooms
Indicates an estimated or not precisely known count of rooms associated with an entity.
-
D.
numberOfBathrooms
Indicates the total count of bathrooms associated with an entity (such as a property or unit).
-
E.
hasBedType
Indicates that an entity (such as a room or accommodation) is associated with a specific type or configuration of bed.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47481663c8190a1110385e5596ab0 |
completed | April 19, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:06 a.m.