Triple
T15891049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Asahi |
E385319
|
entity |
| Predicate | hasWinterActivity |
P57535
|
FINISHED |
| Object | ski touring |
—
|
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: ski touring | Statement: [Mount Asahi, hasWinterActivity, ski touring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinterActivity Context triple: [Mount Asahi, hasWinterActivity, ski touring]
-
A.
hasWinterSports
chosen
Indicates that an entity offers, supports, or is associated with winter sports activities.
-
B.
hasWinterSportsSeason
Indicates that an entity participates in, is associated with, or has a defined period for winter sports activities or competitions.
-
C.
hasPopularWinterSports
Indicates that a place or context is associated with winter sports that are widely practiced, enjoyed, or well-attended.
-
D.
hasFrozenInWinter
Indicates that something becomes or has become frozen during the winter season.
-
E.
hasSnowAndIce
Indicates that the subject is covered with or contains both snow and ice.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.