Triple
T12972963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakiska Ski Resort |
E321448
|
entity |
| Predicate | longestRunLength |
P15978
|
FINISHED |
| Object | about 3.3 km |
—
|
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: about 3.3 km | Statement: [Nakiska Ski Resort, longestRunLength, about 3.3 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longestRunLength Context triple: [Nakiska Ski Resort, longestRunLength, about 3.3 km]
-
A.
mostRuns
Indicates that one entity has scored a greater number of runs than all comparable entities in a given context or set.
-
B.
maximumConsecutiveTerms
Indicates the greatest number of terms that can occur in an unbroken, continuous sequence within a given context or structure.
-
C.
longestDurationAt
Indicates that one entity has the greatest length of time associated with a particular state, event, or activity compared to other relevant entities.
-
D.
largestSpan
Indicates that the referenced entity has the greatest extent or coverage (in distance, time, or range) among a set of comparable spans.
-
E.
maximumSegmentLength
chosen
Indicates the greatest allowable or observed length of a segment within a given context or structure.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:36 p.m.