Triple
T24645948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of South Lake Tahoe |
E610109
|
entity |
| Predicate | nearbySkiResortArea |
P1981
|
FINISHED |
| Object | Kirkwood Mountain Resort area |
—
|
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: Kirkwood Mountain Resort area | Statement: [City of South Lake Tahoe, nearbySkiResortArea, Kirkwood Mountain Resort area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbySkiResortArea Context triple: [City of South Lake Tahoe, nearbySkiResortArea, Kirkwood Mountain Resort area]
-
A.
nearbyResortArea
Indicates that a resort area is located close to or within a short distance of a specified place or entity.
-
B.
hasSkiResortNearby
chosen
Indicates that one location is situated close enough to another location that it can be considered to have a ski resort in its vicinity.
-
C.
skiAreaName
Indicates that an entity has a specific name used to identify a ski area.
-
D.
nearbyResortSection
Indicates that one resort section is located close to another resort section in physical proximity.
-
E.
skiAreaLinkedTo
Indicates that one ski area is connected or associated with another, such as through shared lifts, trails, passes, or coordinated operations.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442a977b08190b44eac040cb90211 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 2:33 a.m.