Triple
T13201484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerto de Cotos |
E314251
|
entity |
| Predicate | typicalWinterConditions |
P10789
|
FINISHED |
| Object | frequent 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: frequent snow | Statement: [Puerto de Cotos, typicalWinterConditions, frequent snow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWinterConditions Context triple: [Puerto de Cotos, typicalWinterConditions, frequent snow]
-
A.
winterCharacteristic
chosen
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
B.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
C.
hasSnowAndIce
Indicates that the subject is covered with or contains both snow and ice.
-
D.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
-
E.
typicalSeaIceCondition
Indicates the usual or characteristic state or properties of sea ice under normal environmental conditions.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:16 p.m.