Triple
T9976399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cascade Lakes |
E196340
|
entity |
| Predicate | roadProximity |
P49834
|
FINISHED |
| Object | immediately adjacent to NY-73 |
—
|
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: immediately adjacent to NY-73 | Statement: [Cascade Lakes, roadProximity, immediately adjacent to NY-73]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadProximity Context triple: [Cascade Lakes, roadProximity, immediately adjacent to NY-73]
-
A.
nearbyMajorRoad
chosen
Indicates that one entity is located close to a significant or heavily used road.
-
B.
nearestRoadHead
Indicates that one location is the closest accessible road endpoint (or road access point) to another location.
-
C.
nearbyHighwayMilepost
Indicates that one entity is located close to a specific highway milepost associated with another entity.
-
D.
nearbyTransit
Indicates that one location has public transportation options situated within a short distance or easy access from it.
-
E.
proximityToLandmark
Indicates a spatial relationship where one entity is located near or close to a specified landmark.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb84d0d3c8190b268582bb79c8973 |
completed | April 2, 2026, 12:29 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:48 p.m.