Triple
T2728455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheppard–Yonge station |
E60250
|
entity |
| Predicate | hasConcourseLevel |
P41910
|
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: [Sheppard–Yonge station, hasConcourseLevel, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConcourseLevel Context triple: [Sheppard–Yonge station, hasConcourseLevel, yes]
-
A.
hasConcourse
Indicates that an entity includes, is connected to, or is served by a concourse area (such as a passageway or central hall).
-
B.
hasLevel
Indicates that an entity possesses or is associated with a particular degree, rank, or stage within an ordered scale or hierarchy.
-
C.
hasNumberOfConcourses
Indicates the relationship specifying how many concourses are associated with a given entity.
-
D.
isMainConcourseOf
Indicates that one concourse serves as the primary or central concourse within a larger facility or complex.
-
E.
coversLevel
Indicates that one entity includes or encompasses a particular level or layer of another entity or system.
- F. None of above. chosen
Provenance (4 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaeaee388190a21e7fa0b8f83546 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd82586f88190a98f60d3247fe2d3 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd949c120819099a9d56eb71a0339 |
completed | March 7, 2026, 7:52 a.m. |
Created at: March 6, 2026, 9:56 p.m.