Triple
T19767022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Arm |
E474784
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Anmore |
—
|
NE NERFINISHED |
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: Anmore | Statement: [Indian Arm, near, Anmore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anmore Context triple: [Indian Arm, near, Anmore]
-
A.
Anmore
chosen
Anmore is a small semi-rural village in Metro Vancouver, British Columbia, known for its forested setting and proximity to outdoor recreation areas.
-
B.
Canmore
Canmore is the online database of Scotland’s national record of the historic environment, documenting archaeological sites, buildings, and maritime heritage.
-
C.
Canmore
Canmore is a mountain town in Alberta, Canada, known for its scenic location in the Canadian Rockies near Banff National Park and its popularity for outdoor recreation.
-
D.
Beaverlodge
Beaverlodge is a small town in northwestern Alberta, Canada, known for its agricultural base and proximity to the city of Grande Prairie.
-
E.
Banff
Banff is a resort town in the Canadian Rockies of Alberta, known for its stunning mountain scenery, hot springs, and role as a gateway to outdoor recreation in Banff National Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653232e508190a7d484c0a1e2939a |
completed | April 20, 2026, 4:24 p.m. |
Created at: April 10, 2026, 1:48 p.m.