Triple
T17689318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outer Harbour |
E440981
|
entity |
| Predicate | cityWaterfrontRole |
P114920
|
FINISHED |
| Object | part of Toronto’s harbour system |
—
|
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: part of Toronto’s harbour system | Statement: [Outer Harbour, cityWaterfrontRole, part of Toronto’s harbour system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityWaterfrontRole Context triple: [Outer Harbour, cityWaterfrontRole, part of Toronto’s harbour system]
-
A.
isCentralWaterfrontOf
Indicates that one location serves as the primary waterfront area or main waterside district of another place.
-
B.
locatedInWaterfrontArea
Indicates that something is situated within a designated waterfront area adjacent to a body of water.
-
C.
hasWaterfrontType
Indicates that an entity is associated with a specific type or category of waterfront (e.g., oceanfront, lakefront, riverfront).
-
D.
associatedWithWaterfront
chosen
Indicates a relationship in which something is located on, adjacent to, or otherwise directly connected with a waterfront area.
-
E.
hasWaterfrontUse
Indicates that an entity is used, designated, or suitable for activities or purposes directly related to a waterfront or shoreline area.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4704a6bb4819083752285baf3b3ee |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:03 a.m.