Triple
T14972146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pigeon Lake (Kawartha Lakes) |
E373346
|
entity |
| Predicate | hasShoreLandUse |
P20797
|
FINISHED |
| Object | seasonal cottages |
—
|
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: seasonal cottages | Statement: [Pigeon Lake (Kawartha Lakes), hasShoreLandUse, seasonal cottages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoreLandUse Context triple: [Pigeon Lake (Kawartha Lakes), hasShoreLandUse, seasonal cottages]
-
A.
hasShorelineUse
chosen
Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
-
B.
hasShoreFeature
Indicates that a shore or coastline possesses a specific physical or environmental feature.
-
C.
hasShoreOn
Indicates that one geographic entity borders or is directly adjacent to the shore of another body of water.
-
D.
hasShorelineUseRestrictions
Indicates that there are specific rules or limitations governing how the shoreline area associated with an entity may be used or developed.
-
E.
hasLongShoreline
Indicates that an entity possesses an extensive or unusually long shoreline relative to typical cases.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e767608190940eb6f16ea97451 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:50 a.m.