Triple
T7039464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rutland, Vermont |
E163469
|
entity |
| Predicate | averageWinterActivity |
P19624
|
FINISHED |
| Object | skiing |
—
|
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: skiing | Statement: [Rutland, Vermont, averageWinterActivity, skiing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWinterActivity Context triple: [Rutland, Vermont, averageWinterActivity, skiing]
-
A.
hasWinterSports
Indicates that an entity offers, supports, or is associated with winter sports activities.
-
B.
hasPopularWinterSports
chosen
Indicates that a place or context is associated with winter sports that are widely practiced, enjoyed, or well-attended.
-
C.
hasWinterSportsSeason
Indicates that an entity participates in, is associated with, or has a defined period for winter sports activities or competitions.
-
D.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
-
E.
winterCharacteristic
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bb602081908bfa6186a1f5a4b4 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:36 p.m.