Triple
T7505467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chapel Falls |
E177375
|
entity |
| Predicate | proximityToLake |
P17985
|
FINISHED |
| Object | near Lake Superior shoreline |
—
|
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: near Lake Superior shoreline | Statement: [Chapel Falls, proximityToLake, near Lake Superior shoreline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToLake Context triple: [Chapel Falls, proximityToLake, near Lake Superior shoreline]
-
A.
hasNearbyLake
chosen
Indicates that one entity is located close to or in the vicinity of a lake.
-
B.
lakeTypeNearby
Indicates that one entity is located near another entity that is classified as a particular type of lake.
-
C.
isInLake
Indicates that one entity is located within the body of water defined as a lake.
-
D.
hasNearbyWater
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
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_69c69f276b108190af2cc790b6554544 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5b5fcd88190ab4ab0ba96a6aa4b |
completed | March 27, 2026, 9:25 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d44e9481909813e073b194f6f4 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:44 p.m.