Triple
T5294401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korean King Sejong Station |
E119817
|
entity |
| Predicate | averageSummerTemperatureC |
P63362
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Korean King Sejong Station, averageSummerTemperatureC, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageSummerTemperatureC Context triple: [Korean King Sejong Station, averageSummerTemperatureC, 1]
-
A.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
B.
averageWarmestMonth
Indicates the relationship between a place and the month in which its long-term average temperature is highest.
-
C.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
D.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
E.
averageMaxTemperatureWarmestMonth
Indicates the highest average temperature recorded in the warmest month of a given time period or location.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69bd86800630819096dad2eb2248c372 |
completed | March 20, 2026, 5:40 p.m. |
Created at: March 20, 2026, 1:52 p.m.