Triple
T11954319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Symonds College |
E284511
|
entity |
| Predicate | hasBoardingFacility |
P63715
|
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: [Peter Symonds College, hasBoardingFacility, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardingFacility Context triple: [Peter Symonds College, hasBoardingFacility, yes]
-
A.
hasBoardingAreaFor
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
B.
hasBoardingOption
chosen
Indicates that an entity offers or is associated with a particular way or method by which passengers or items can board or be taken on.
-
C.
hasPassengerTerminalFacilities
Indicates that an entity provides facilities or infrastructure specifically intended for handling and serving passengers.
-
D.
hasBoardingType
Indicates the specific manner or method by which an entity is boarded or accessed (e.g., how passengers or items are taken on).
-
E.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90365da288190a132703df563de23 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.