Triple
T432137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sea of Azov |
E9735
|
entity |
| Predicate | freezesIn |
P4500
|
FINISHED |
| Object | winter in severe cold spells |
—
|
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: winter in severe cold spells | Statement: [Sea of Azov, freezesIn, winter in severe cold spells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: freezesIn Context triple: [Sea of Azov, freezesIn, winter in severe cold spells]
-
A.
requiresFrostFreeSeason
Indicates that the subject depends on a period without frost to grow, develop, or function properly.
-
B.
hasFrieze
Indicates that one entity features or is adorned with a frieze associated with another entity.
-
C.
surfaceFreezesPartiallyIn
chosen
Indicates that a surface undergoes a freezing process in which only part of it becomes frozen within a given medium, environment, or container.
-
D.
isCryogenic
Indicates that something operates at, is designed for, or involves extremely low (cryogenic) temperatures.
-
E.
hasIcebergs
Indicates that one entity (typically a body of water or region) contains or is characterized by the presence of icebergs.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eef07e748190b05392778f3de980 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd9264c8190b92f9a50348e5541 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.