Triple
T26070750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frognerseteren station |
E657536
|
entity |
| Predicate | winterUsage |
P10789
|
FINISHED |
| Object | popular for skiing access |
—
|
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: popular for skiing access | Statement: [Frognerseteren station, winterUsage, popular for skiing access]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterUsage Context triple: [Frognerseteren station, winterUsage, popular for skiing access]
-
A.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
B.
winterCharacteristic
chosen
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
C.
winterAccessMode
Indicates how access to something is configured, permitted, or restricted specifically during the winter season.
-
D.
winterFrequency
Indicates how often the related event, condition, or phenomenon occurs during the winter season.
-
E.
winterSession
Indicates that an event, course, or activity takes place during a designated winter academic or seasonal session.
- 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_69ee5bbe539081909efc7f9dd7c1b53c |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f606ca69b08190977693fd1f8e8ae4 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f5aff889988190ad10bcf1a280f717 |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 7:28 p.m.