Triple
T19147745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oymyakon |
E468723
|
entity |
| Predicate | winterDaylight |
P10789
|
FINISHED |
| Object | very short days in winter |
—
|
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: very short days in winter | Statement: [Oymyakon, winterDaylight, very short days in winter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterDaylight Context triple: [Oymyakon, winterDaylight, very short days in winter]
-
A.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
B.
winterSession
Indicates that an event, course, or activity takes place during a designated winter academic or seasonal session.
-
C.
winterFrequency
Indicates how often the related event, condition, or phenomenon occurs during the winter season.
-
D.
winterCharacteristic
chosen
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
E.
timeInWinter
Indicates that the specified time interval occurs during the winter season.
- 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.