Triple
T18863718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Washington Auto Road |
E461377
|
entity |
| Predicate | isClosedInWinter |
P105428
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mount Washington Auto Road, isClosedInWinter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isClosedInWinter Context triple: [Mount Washington Auto Road, isClosedInWinter, true]
-
A.
isOftenClosedInSeason
chosen
Indicates that something, such as a place or facility, is frequently not open or available during a particular season.
-
B.
hasFrozenInWinter
Indicates that something becomes or has become frozen during the winter season.
-
C.
closedOrSnowCoveredIn
Indicates that something is either closed or covered by snow within a specified location or area.
-
D.
hasLongWinterSeason
Indicates that the referenced entity experiences a winter season that lasts for an extended or unusually long period of time.
-
E.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c2a304d4819092f14b7932d01afe |
completed | April 20, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69e48d2166b88190add38de96cedc65c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:57 a.m.