Triple
T8819451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sela Pass |
E209863
|
entity |
| Predicate | roadCondition |
P78490
|
FINISHED |
| Object | often affected by 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: often affected by snow | Statement: [Sela Pass, roadCondition, often affected by snow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadCondition Context triple: [Sela Pass, roadCondition, often affected by snow]
-
A.
hasRoadCondition
chosen
Indicates that a specified road segment possesses or is characterized by a particular condition or state (e.g., quality, surface, or status).
-
B.
roadEnvironment
Indicates that the relationship or action occurs within, is influenced by, or is specifically associated with a road or roadway environment.
-
C.
onRoad
Indicates that one entity is located on, traveling along, or otherwise situated upon a road.
-
D.
roadAffected
Indicates that a road is impacted or disrupted by a condition, event, or action, such as construction, accidents, or adverse weather.
-
E.
roadSide
Indicates that one entity is located along, beside, or immediately adjacent to a road.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc600e6e2881908934cbff0ab5d6fd |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:46 p.m.