Triple
T19147721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oymyakon |
E468723
|
entity |
| Predicate | recordLowTemperatureYear |
P134603
|
FINISHED |
| Object | 1933 |
—
|
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: 1933 | Statement: [Oymyakon, recordLowTemperatureYear, 1933]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordLowTemperatureYear Context triple: [Oymyakon, recordLowTemperatureYear, 1933]
-
A.
recordLowTemperature
Indicates that a specified temperature value is the lowest recorded temperature for a given entity, location, or time period.
-
B.
averageAnnualLowTemperature
Indicates the typical lowest temperature value recorded per year for a given place or period, averaged over multiple years.
-
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_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. |
| PDg | Predicate description generation | batch_69e4bfe9ef7081908a74a57d1fc731ea |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:06 p.m.