Triple
T4860862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Street stop |
E108654
|
entity |
| Predicate | servesIntersection |
P59446
|
FINISHED |
| Object | Spadina Avenue and College Street |
—
|
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: Spadina Avenue and College Street | Statement: [College Street stop, servesIntersection, Spadina Avenue and College Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesIntersection Context triple: [College Street stop, servesIntersection, Spadina Avenue and College Street]
-
A.
servesUse
Indicates that one entity is used by or functions to serve the purpose or needs of another entity.
-
B.
servesOn
Indicates that one entity performs duties, functions, or holds a role as a member within another entity, such as a group, body, or organization.
-
C.
servesUnder
Indicates that one entity works in a subordinate role under the authority, command, or supervision of another entity.
-
D.
fieldIntersection
Indicates that two or more fields or domains share a common overlapping area or set of elements.
-
E.
isServedAt
Indicates that something (such as food, drink, or a service) is provided or made available at a particular place or venue.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d5e247c8190b6ae4e9b529f0345 |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6cfa8bd881908e376ab286759cc2 |
completed | March 20, 2026, 3:51 p.m. |
Created at: March 20, 2026, 1:26 p.m.