Triple
T2876365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breckenridge Ski Resort |
E56887
|
entity |
| Predicate | offersSnowboarding |
P27566
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Breckenridge Ski Resort, offersSnowboarding, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersSnowboarding Context triple: [Breckenridge Ski Resort, offersSnowboarding, yes]
-
A.
snowboardVenue
Indicates the location or venue where snowboarding takes place or is held.
-
B.
hasPopularWinterSports
Indicates that a place or context is associated with winter sports that are widely practiced, enjoyed, or well-attended.
-
C.
hasMountainSport
chosen
Indicates that an entity is associated with or offers a particular mountain-related sport or activity.
-
D.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
E.
skiAreaType
Indicates the specific type or classification of a ski area associated with an entity (e.g., resort, backcountry, terrain park).
- 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe0061d048190bb1e5a01e7ceb0e2 |
completed | March 7, 2026, 8:21 a.m. |
| PD | Predicate disambiguation | batch_69abdd142e4c8190b424cb0c5ff40d04 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:03 p.m.