Triple
T7185467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Toronto Junction vicinity |
E167557
|
entity |
| Predicate | hasHistoricalLandUse |
P44099
|
FINISHED |
| Object | rail yards |
—
|
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: rail yards | Statement: [West Toronto Junction vicinity, hasHistoricalLandUse, rail yards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalLandUse Context triple: [West Toronto Junction vicinity, hasHistoricalLandUse, rail yards]
-
A.
hasHistoricalLandCover
Indicates that an entity is associated with information about the land cover that existed in a specified area during a past time period.
-
B.
formerLandUse
chosen
Indicates the type of land use that characterized a location prior to its current or present use.
-
C.
hasHistoricLandGrants
Indicates that an entity has been granted land through one or more historically significant official land grants.
-
D.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
E.
hasHistoricVillageArea
Indicates that an entity includes or is associated with an area recognized as a historic village or traditional settlement zone.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:49 p.m.