Triple
T20086647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teddington Memorial Hospital |
E496148
|
entity |
| Predicate | hasBeds |
P29715
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Teddington Memorial Hospital, hasBeds, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeds Context triple: [Teddington Memorial Hospital, hasBeds, yes]
-
A.
hasBedType
Indicates that an entity (such as a room or accommodation) is associated with a specific type or configuration of bed.
-
B.
bedCount
chosen
Indicates the number of beds associated with an entity, such as a room, facility, or accommodation.
-
C.
numberOfBedrooms
Indicates the quantity of bedrooms associated with a given property or dwelling.
-
D.
beds
Indicates that one entity provides or designates a place for another entity to sleep or rest.
-
E.
hasBedMaterial
Indicates that one entity has, contains, or is characterized by a particular bed material (e.g., the substance forming the base or bedding of that 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655ba40c8190adea0e271a1249cf |
completed | April 20, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:04 p.m.