Triple
T7816408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asaka, Saitama |
E181016
|
entity |
| Predicate | hottestMonth |
P47011
|
FINISHED |
| Object | August |
—
|
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: August | Statement: [Asaka, Saitama, hottestMonth, August]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hottestMonth Context triple: [Asaka, Saitama, hottestMonth, August]
-
A.
averageWarmestMonth
chosen
Indicates the relationship between a place and the month in which its long-term average temperature is highest.
-
B.
averageMaxTemperatureWarmestMonth
Indicates the highest average temperature recorded in the warmest month of a given time period or location.
-
C.
wettestMonths
Indicates the months during which a location experiences the highest amount of precipitation compared to other months.
-
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_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.