Triple
T23495160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mouthe |
E571685
|
entity |
| Predicate | minimumRecordedTemperatureDate |
P152609
|
FINISHED |
| Object | 17 January 1985 |
—
|
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: 17 January 1985 | Statement: [Mouthe, minimumRecordedTemperatureDate, 17 January 1985]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumRecordedTemperatureDate Context triple: [Mouthe, minimumRecordedTemperatureDate, 17 January 1985]
-
A.
recordLowTemperature
Indicates that a specified temperature value is the lowest recorded temperature for a given entity, location, or time period.
-
B.
recordLowTemperatureYear
Indicates the year in which the lowest recorded temperature for a given place or entity occurred.
-
C.
minimumWinterTemperature
Indicates the lowest temperature typically experienced during the winter season for the subject entity.
-
D.
averageMinTemperatureColdestMonth
Indicates the lowest average minimum temperature recorded during the coldest month in a given location or period.
-
E.
averageColdestMonth
Indicates the month in which an entity experiences the lowest average temperature over a given period.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7def8ac8190ade511299078d55b |
completed | April 29, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:05 p.m.