Triple
T2320041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shortgrass prairie |
E51158
|
entity |
| Predicate | fireRegime |
P20871
|
FINISHED |
| Object | frequent low-intensity fires |
—
|
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: frequent low-intensity fires | Statement: [Shortgrass prairie, fireRegime, frequent low-intensity fires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireRegime Context triple: [Shortgrass prairie, fireRegime, frequent low-intensity fires]
-
A.
hasFireRegime
chosen
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
-
B.
wildfireRisk
Indicates the likelihood or potential severity of wildfires occurring in a given area or under specific conditions.
-
C.
fires
Indicates that an agent initiates the discharge or ignition of something, such as a weapon, engine, or explosive device, causing it to operate or go off.
-
D.
fireModes
Indicates the different ways or settings in which a weapon or device can be fired or operated.
-
E.
fireAdaptation
Indicates that an entity possesses traits or mechanisms that enable it to survive, reproduce, or otherwise benefit in environments where fire occurs.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.