Triple
T7816409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asaka, Saitama |
E181016
|
entity |
| Predicate | coldestMonth |
P47012
|
FINISHED |
| Object | January |
—
|
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: January | Statement: [Asaka, Saitama, coldestMonth, January]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coldestMonth Context triple: [Asaka, Saitama, coldestMonth, January]
-
A.
averageColdestMonth
chosen
Indicates the month in which an entity experiences the lowest average temperature over a given period.
-
B.
averageMinTemperatureColdestMonth
Indicates the lowest average minimum temperature recorded during the coldest month in a given location or period.
-
C.
coldestSeason
Indicates the season during which a place or region experiences its lowest typical temperatures compared to other seasons.
-
D.
averageJanuaryLowTemperature
Indicates the typical minimum daily temperature experienced in a location during the month of January.
-
E.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf96ea6d881908eff5f750e0f6700 |
completed | March 30, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:39 p.m.