Triple
T12428126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port de la Bonaigua |
E296950
|
entity |
| Predicate | hasSeasonalIssues |
P15928
|
FINISHED |
| Object | occasional winter closures |
—
|
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: occasional winter closures | Statement: [Port de la Bonaigua, hasSeasonalIssues, occasional winter closures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalIssues Context triple: [Port de la Bonaigua, hasSeasonalIssues, occasional winter closures]
-
A.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
B.
hasSeasonalStatus
chosen
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
-
C.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
-
D.
affectedSeason
Indicates that one entity has an influence on, or causes a change in, a particular season.
-
E.
hasSeasonalHighlight
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94df948308190ace333230a4a3b38 |
completed | April 10, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69d94d391c548190996a8c698357f273 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.