Triple
T12751488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolomyazhsky Bridge |
E304742
|
entity |
| Predicate | hasClimateOfArea |
P193
|
FINISHED |
| Object | humid continental climate |
—
|
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: humid continental climate | Statement: [Kolomyazhsky Bridge, hasClimateOfArea, humid continental climate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClimateOfArea Context triple: [Kolomyazhsky Bridge, hasClimateOfArea, humid continental climate]
-
A.
hasClimate
chosen
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
B.
hasClimateContext
Indicates that something is associated with, influenced by, or relevant to climate-related conditions, factors, or considerations.
-
C.
shareClimateZones
Indicates that two entities are located in regions classified under the same climate zone or zones.
-
D.
climatologicalRegion
Indicates that one entity is a climatological region associated with, or characterizing the climate of, another entity.
-
E.
hasMediterraneanClimate
Indicates that a place experiences a Mediterranean climate, typically characterized by mild, wet winters and hot, dry summers.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.