Triple
T2758083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | York University station |
E61152
|
entity |
| Predicate | hasPublicWashrooms |
P1976
|
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: [York University station, hasPublicWashrooms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicWashrooms Context triple: [York University station, hasPublicWashrooms, yes]
-
A.
hasRestrooms
chosen
Indicates that a place or facility provides access to restroom or toilet amenities.
-
B.
hasPublicSpaces
Indicates that an entity includes or provides areas that are accessible and usable by the general public.
-
C.
hasPublicSpaceAlong
Indicates that a public space (such as a park, plaza, or walkway) is located adjacent to or runs alongside the referenced feature or element.
-
D.
hasPublicHouse
Indicates that one entity possesses, operates, or is associated with a public house (such as a bar or pub) as part of its facilities or holdings.
-
E.
numberOfBathrooms
Indicates the total count of bathrooms associated with an entity (such as a property or unit).
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb8ba4688190b401b6eb5b734ac6 |
completed | March 7, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69abd82de7f48190acd614f28644c6da |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:57 p.m.