Triple
T19572628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konza Prairie Biological Station |
E489756
|
entity |
| Predicate | disturbanceRegime |
P20871
|
FINISHED |
| Object | prescribed fire |
—
|
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: prescribed fire | Statement: [Konza Prairie Biological Station, disturbanceRegime, prescribed fire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disturbanceRegime Context triple: [Konza Prairie Biological Station, disturbanceRegime, prescribed fire]
-
A.
typicalDisturbanceRegime
Indicates the characteristic pattern, frequency, and intensity of disturbances (e.g., fire, storms, pests) that typically affect an entity or system over time.
-
B.
disturbanceLevel
Indicates the degree or intensity of disruption, interference, or deviation from a normal or stable state in a given context.
-
C.
occursInRegime
Indicates that an event, process, or phenomenon takes place within a specific regime, context, or operating condition.
-
D.
disruptsContinuityOf
Indicates that one entity interrupts, breaks, or otherwise prevents the ongoing, uninterrupted progression or sequence of another entity or process.
-
E.
hasFireRegime
chosen
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402228488190b5649d4bbd34d019 |
completed | April 20, 2026, 3:02 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:42 p.m.