Triple
T38275566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ross Archipelago |
E1021941
|
entity |
| Predicate | hasSeaIceFeature |
P21866
|
FINISHED |
| Object | seasonal sea ice |
—
|
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: seasonal sea ice | Statement: [Ross Archipelago, hasSeaIceFeature, seasonal sea ice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeaIceFeature Context triple: [Ross Archipelago, hasSeaIceFeature, seasonal sea ice]
-
A.
hasSeaIce
Indicates that one entity possesses, contains, or is covered by sea ice in relation to another context or location.
-
B.
hasSeaIceExtent
Indicates that a specified area or region possesses a measurable amount or coverage of sea ice over a given space or time.
-
C.
hasNearbyIceFeature
Indicates that one entity is located close to another entity that is characterized as an ice-related feature (such as ice, glaciers, or icy terrain).
-
D.
hasIcebergs
Indicates that one entity (typically a body of water or region) contains or is characterized by the presence of icebergs.
-
E.
hasTypicalSeaIceType
chosen
Indicates the characteristic or commonly occurring type of sea ice associated with a given location or context.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00cbae75988190974f5b45a2e62326 |
completed | May 10, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_6a00cabe4c5881909cca5efbe494e0d1 |
completed | May 10, 2026, 6:13 p.m. |
Created at: May 3, 2026, 4:30 p.m.