Triple
T4994897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Squamish |
E112221
|
entity |
| Predicate | locatedBetween |
P1262
|
FINISHED |
| Object | Whistler |
E292096
|
NE 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: Whistler | Statement: [Squamish, locatedBetween, Whistler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Whistler Context triple: [Squamish, locatedBetween, Whistler]
-
A.
Whistler
Whistler was the internal codename used by Microsoft during the development of the Windows XP operating system.
-
B.
Whistler
chosen
Whistler is a renowned resort town in British Columbia, Canada, famous for its world-class skiing, mountain biking, and outdoor recreation.
-
C.
Whitemark
Whitemark is the principal township and administrative centre of Flinders Island in Tasmania, Australia.
-
D.
Banff
Banff is a historic town in Aberdeenshire, Scotland, known for its coastal setting on the Moray Firth and its well-preserved Georgian architecture.
-
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 (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_69bd4432b32c81909f3b3c6bd10f0653 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd729e9fb48190a467b6a373a73367 |
completed | March 20, 2026, 4:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be92557c508190a8c27b974906999f |
completed | March 21, 2026, 12:43 p.m. |
Created at: March 20, 2026, 1:34 p.m.