Triple
T332960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irish Sea |
E6662
|
entity |
| Predicate | seaSurfaceTemperatureRange |
P9975
|
FINISHED |
| Object | approximately 5 to 15 degrees Celsius |
—
|
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: approximately 5 to 15 degrees Celsius | Statement: [Irish Sea, seaSurfaceTemperatureRange, approximately 5 to 15 degrees Celsius]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seaSurfaceTemperatureRange Context triple: [Irish Sea, seaSurfaceTemperatureRange, approximately 5 to 15 degrees Celsius]
-
A.
surfaceTemperatureRange
chosen
Indicates the range between the minimum and maximum surface temperatures observed or allowed for an entity.
-
B.
waterTemperatureType
Indicates the classification or category of a water body’s temperature (e.g., cold, warm, hot) associated with an entity or context.
-
C.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
D.
seaIceMinimumExtent
Indicates the smallest recorded spatial coverage of sea ice over a specified period or region.
-
E.
seaIceMaximumExtent
Indicates the greatest spatial coverage or area that sea ice reaches during its annual or seasonal cycle.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac4d9d081908a624464e450fb0e |
completed | Feb. 28, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69a2e94d99cc8190a112e4b630ec63c1 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.