Triple
T22978270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cortaillod |
E571385
|
entity |
| Predicate | hasLakeShoreUse |
P20797
|
FINISHED |
| Object | residential area |
—
|
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: residential area | Statement: [Cortaillod, hasLakeShoreUse, residential area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeShoreUse Context triple: [Cortaillod, hasLakeShoreUse, residential area]
-
A.
hasLakeshore
Indicates that one entity is located along or directly borders the shore of a lake associated with another entity.
-
B.
hasShorelineUse
chosen
Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
-
C.
usesLakeFor
Indicates that an entity utilizes a lake as a resource or setting for some purpose, activity, or function.
-
D.
hasShoreFeature
Indicates that a shore or coastline possesses a specific physical or environmental feature.
-
E.
hasLandscapeUse
Indicates that something is used or intended to be used within a landscape or landscaping context.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18293f830819095cca91af7abd742 |
completed | April 29, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:49 p.m.