Triple
T25736512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catatumbo lightning |
E645390
|
entity |
| Predicate | averageFrequencyPerYear |
P16914
|
FINISHED |
| Object | around 260 nights per year |
—
|
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: around 260 nights per year | Statement: [Catatumbo lightning, averageFrequencyPerYear, around 260 nights per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageFrequencyPerYear Context triple: [Catatumbo lightning, averageFrequencyPerYear, around 260 nights per year]
-
A.
averageRecurrenceInterval
Indicates the typical time span between successive occurrences of the same type of event.
-
B.
performedFrequency
chosen
Indicates how often an action or activity is carried out within a given time period.
-
C.
averageYearError
Indicates the average deviation, in years, between predicted and actual temporal values across instances.
-
D.
averageAge
Indicates the mean age value calculated from a group of entities or individuals.
-
E.
hasSeasonFrequency
Indicates how often something occurs or is scheduled within a specific 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fcbf71308190a81518c504d5632d |
completed | May 2, 2026, 1:31 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 11:27 p.m.