Triple
T31011504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eldora Mountain Resort |
E790219
|
entity |
| Predicate | distanceFromBoulder |
P203482
|
FINISHED |
| Object | approximately 21 miles |
—
|
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: approximately 21 miles | Statement: [Eldora Mountain Resort, distanceFromBoulder, approximately 21 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBoulder Context triple: [Eldora Mountain Resort, distanceFromBoulder, approximately 21 miles]
-
A.
distanceFromDenver
Indicates the measured distance between a given location and Denver.
-
B.
distanceToFortCollins
Indicates the spatial distance between a given entity’s location and the city of Fort Collins.
-
C.
distanceFromSaltLakeCity
Indicates the measured distance between a given location and Salt Lake City.
-
D.
distanceToGreeley
Indicates the measured distance between a given entity or location and Greeley.
-
E.
approxDistanceToColoradoSprings
Indicates that one entity is located at an approximate physical distance from Colorado Springs.
- F. None of above. chosen
Provenance (4 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a018f9c7cf88190adc5daf3806f2077 |
completed | May 11, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_6a018ca4e0e481908091f0c1f8a4c31b |
completed | May 11, 2026, 8 a.m. |
| PDg | Predicate description generation | batch_6a018f9bd91c8190980967b4eef78a58 |
completed | May 11, 2026, 8:13 a.m. |
Created at: April 29, 2026, 8:57 p.m.