Triple
T19147720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oymyakon |
E468723
|
entity |
| Predicate | recordLowTemperatureInFahrenheit |
P15651
|
FINISHED |
| Object | −89.9 °F |
—
|
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: −89.9 °F | Statement: [Oymyakon, recordLowTemperatureInFahrenheit, −89.9 °F]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordLowTemperatureInFahrenheit Context triple: [Oymyakon, recordLowTemperatureInFahrenheit, −89.9 °F]
-
A.
recordLowTemperature
chosen
Indicates that a specified temperature value is the lowest recorded temperature for a given entity, location, or time period.
-
B.
minimumWinterTemperature
Indicates the lowest temperature typically experienced during the winter season for the subject entity.
-
C.
averageAnnualLowTemperature
Indicates the typical lowest temperature value recorded per year for a given place or period, averaged over multiple years.
-
D.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
E.
averageJanuaryLowTemperature
Indicates the typical minimum daily temperature experienced in a location during the month of January.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e97a79a48190b243553023bf9081 |
completed | April 20, 2026, 8:53 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b475d88190a8c15e8eb01dbfef |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.