Triple
T31536947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenner |
E804630
|
entity |
| Predicate | hasWinterSportInfrastructure |
P149853
|
FINISHED |
| Object | groomed ski pistes |
—
|
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: groomed ski pistes | Statement: [Jenner, hasWinterSportInfrastructure, groomed ski pistes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinterSportInfrastructure Context triple: [Jenner, hasWinterSportInfrastructure, groomed ski pistes]
-
A.
hasWinterSports
Indicates that an entity offers, supports, or is associated with winter sports activities.
-
B.
hasWinterSportsResort
Indicates that a location or entity possesses or hosts a resort specifically dedicated to winter sports activities.
-
C.
hasWinterSportsSeason
Indicates that an entity participates in, is associated with, or has a defined period for winter sports activities or competitions.
-
D.
hasPopularWinterSports
Indicates that a place or context is associated with winter sports that are widely practiced, enjoyed, or well-attended.
-
E.
isSkiDestination
chosen
Indicates that a place serves as a location suitable or commonly used for skiing activities.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 30, 2026, 10:04 p.m.