Triple
T20238234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheakamus Lake |
E498209
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Whistler |
—
|
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: Whistler | Statement: [Cheakamus Lake, locatedNear, Whistler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Whistler Context triple: [Cheakamus Lake, locatedNear, Whistler]
-
A.
Whistler
chosen
Whistler is a renowned resort town in British Columbia, Canada, famous for its world-class skiing, mountain biking, and outdoor recreation.
-
B.
Whistler
Whistler is a small unincorporated community located in Mobile County, Alabama, known historically as a railroad town.
-
C.
Whistler
Whistler was the internal codename used by Microsoft during the development of the Windows XP operating system.
-
D.
Whistler
Whistler is a surname most famously associated with the American-born artist James McNeill Whistler and his relatives, including Beatrice Whistler.
-
E.
Whistler
Whistler is a character from the television series "Prison Break," known for his mysterious background and involvement in complex prison escape plots.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6716b4c148190bf663b8a747fbfa5 |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.