Triple
T36375143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glanbrook, Ontario |
E895878
|
entity |
| Predicate | hasLandUsePolicyIssue |
P141795
|
FINISHED |
| Object | urban sprawl and farmland preservation |
—
|
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: urban sprawl and farmland preservation | Statement: [Glanbrook, Ontario, hasLandUsePolicyIssue, urban sprawl and farmland preservation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUsePolicyIssue Context triple: [Glanbrook, Ontario, hasLandUsePolicyIssue, urban sprawl and farmland preservation]
-
A.
landUseIssues
chosen
Indicates conflicts, problems, or concerns arising from how land is used, managed, or designated.
-
B.
hasPolicyIssue
Indicates that an entity is associated with a specific policy-related problem, concern, or noncompliance.
-
C.
hasLandUsePressure
Indicates that an area or entity is subject to demands or stresses from human or other uses of land that may affect its condition or availability.
-
D.
hasLandUseSystem
Indicates that an entity is associated with or characterized by a particular system or pattern of land use.
-
E.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
- 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_69f76e5115588190ad8738860b7bc68b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffada24d188190a576a02dc280a7fb |
completed | May 9, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69ffad46d6ac819081772f408b1389d5 |
completed | May 9, 2026, 9:55 p.m. |
Created at: May 3, 2026, 4:10 p.m.