Triple
T573651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bering Sea |
E13715
|
entity |
| Predicate | hasSeasonalFeature |
P955
|
FINISHED |
| Object | extensive sea ice in winter |
—
|
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: extensive sea ice in winter | Statement: [Bering Sea, hasSeasonalFeature, extensive sea ice in winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalFeature Context triple: [Bering Sea, hasSeasonalFeature, extensive sea ice in winter]
-
A.
hasSeasonalPattern
chosen
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
B.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
C.
hasImportantSeason
Indicates that an entity experiences a particular season or time period that is especially significant or notable for it.
-
D.
hasSeasonalDecorations
Indicates that an entity is adorned with decorations that are specific to a particular season or holiday period.
-
E.
seasonCharacterization
Indicates how a particular season is described, defined, or characterized in terms of its qualities or attributes.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b4ae0988190bdd0ad428b784d85 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.