Triple
T4079156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 8.2 kiloyear event |
E87434
|
entity |
| Predicate | temperatureAnomaly |
P23013
|
FINISHED |
| Object | cooling of about 1 to 3 degrees Celsius in some regions |
—
|
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: cooling of about 1 to 3 degrees Celsius in some regions | Statement: [8.2 kiloyear event, temperatureAnomaly, cooling of about 1 to 3 degrees Celsius in some regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temperatureAnomaly Context triple: [8.2 kiloyear event, temperatureAnomaly, cooling of about 1 to 3 degrees Celsius in some regions]
-
A.
globalTemperatureAnomaly
chosen
Indicates the deviation of the Earth's average temperature from a defined long-term baseline or reference period.
-
B.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
C.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
D.
temperatureRangeDifference
Indicates the difference between two temperature ranges, typically measuring how much one range is higher or lower than another.
-
E.
notableWeather
Indicates that a location experiences weather conditions that are significant, unusual, or noteworthy in some way.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc4e95b08190bd1ee8f6d3a9613c |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.