Triple
T33816271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Route 67 (Arizona) |
E866685
|
entity |
| Predicate | winterClosure |
P103010
|
FINISHED |
| Object | closed in winter due to snow |
—
|
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: closed in winter due to snow | Statement: [State Route 67 (Arizona), winterClosure, closed in winter due to snow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterClosure Context triple: [State Route 67 (Arizona), winterClosure, closed in winter due to snow]
-
A.
winterSession
Indicates that an event, course, or activity takes place during a designated winter academic or seasonal session.
-
B.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
C.
winterSeason
Indicates that the time, event, or condition occurs during or is specifically associated with the winter season.
-
D.
winterAccessMode
chosen
Indicates how access to something is configured, permitted, or restricted specifically during the winter season.
-
E.
winterTouristSeason
Indicates that the relationship or context occurs during the winter period when tourism activity is at its peak or is specifically targeted.
- 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_69f349911a8c81908478662194b23d8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fff324ac8190a2937cae665d109d |
completed | May 3, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:46 a.m.