Triple
T911074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Siberian Sea |
E19658
|
entity |
| Predicate | seaSurfaceFrozen |
P4995
|
FINISHED |
| Object | most of the year |
—
|
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: most of the year | Statement: [East Siberian Sea, seaSurfaceFrozen, most of the year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seaSurfaceFrozen Context triple: [East Siberian Sea, seaSurfaceFrozen, most of the year]
-
A.
hasSeaIce
chosen
Indicates that one entity possesses, contains, or is covered by sea ice in relation to another context or location.
-
B.
hasIcebergs
Indicates that one entity (typically a body of water or region) contains or is characterized by the presence of icebergs.
-
C.
hasSeaIceExtent
Indicates that a specified area or region possesses a measurable amount or coverage of sea ice over a given space or time.
-
D.
snowCover
Indicates that one entity is covered by or blanketed with snow.
-
E.
waterIceLocation
Indicates the spatial location or presence of water ice relative to a specified place or object.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2f605bc8190a5245aa2ca55cf43 |
completed | March 1, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69a4b2918ea881908698020b995a8eae |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.