Triple
T3180240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glenn Highway |
E66565
|
entity |
| Predicate | snowConditions |
P38722
|
FINISHED |
| Object | subject to winter snow and ice |
—
|
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: subject to winter snow and ice | Statement: [Glenn Highway, snowConditions, subject to winter snow and ice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: snowConditions Context triple: [Glenn Highway, snowConditions, subject to winter snow and ice]
-
A.
snowCover
Indicates that one entity is covered by or blanketed with snow.
-
B.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
C.
winterStatus
chosen
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
D.
winterCharacteristic
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
E.
snowRemovalBy
Indicates that one entity performs or is responsible for removing snow from another entity or location.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada69f2d108190847922795e7b6687 |
completed | March 8, 2026, 4:41 p.m. |
| PD | Predicate disambiguation | batch_69ad9e02677c8190a21d93b1259b2761 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.