Triple
T5294402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korean King Sejong Station |
E119817
|
entity |
| Predicate | averageWinterTemperatureC |
P4814
|
FINISHED |
| Object | -6 |
—
|
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: -6 | Statement: [Korean King Sejong Station, averageWinterTemperatureC, -6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWinterTemperatureC Context triple: [Korean King Sejong Station, averageWinterTemperatureC, -6]
-
A.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
B.
averageWinterHighF
Indicates the typical or mean high temperature, measured in degrees Fahrenheit, during the winter season for the referenced entity.
-
C.
averageTemperature
chosen
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
D.
averageColdestMonth
Indicates the month in which an entity experiences the lowest average temperature over a given period.
-
E.
averageMinTemperatureColdestMonth
Indicates the lowest average minimum temperature recorded during the coldest month in a given location or period.
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8682d18c8190bbb35cc75c8a7c12 |
completed | March 20, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69bd844dfdac819086efedd1cbebff84 |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:52 p.m.