Triple
T5453188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London St Pancras to Sheffield |
E122415
|
entity |
| Predicate | onboardFacility |
P12416
|
FINISHED |
| Object | toilets |
—
|
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: toilets | Statement: [London St Pancras to Sheffield, onboardFacility, toilets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onboardFacility Context triple: [London St Pancras to Sheffield, onboardFacility, toilets]
-
A.
basedOnFacility
Indicates that something is determined, derived, or decided according to the characteristics, rules, or conditions of a particular facility.
-
B.
onboardPlatform
Indicates that an entity is being added, integrated, or enrolled onto a particular platform so it can start operating or participating there.
-
C.
servesFacility
Indicates that one entity provides services or support to a particular facility as its client, target, or area of operation.
-
D.
findingOnFacilities
Indicates a relationship where an inspection or assessment identifies a specific issue, observation, or result associated with particular facilities.
-
E.
hasFacilities
chosen
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
- 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.