Triple
T3808687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rim Fire 2013 (affected area) |
E93074
|
entity |
| Predicate | affectedFeature |
P44908
|
FINISHED |
| Object | forest vegetation |
—
|
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: forest vegetation | Statement: [Rim Fire 2013 (affected area), affectedFeature, forest vegetation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedFeature Context triple: [Rim Fire 2013 (affected area), affectedFeature, forest vegetation]
-
A.
affectedEntity
Indicates that an entity is the one that is impacted, influenced, or acted upon as a result of an event, action, or process.
-
B.
affectedFunction
Indicates that one entity has an impact on, alters, or impairs the operation or behavior of another entity’s function.
-
C.
affectedStructure
chosen
Indicates that one entity is the structure, component, or part that is impacted, altered, or influenced by another entity or event.
-
D.
affectedProvision
Indicates that a particular legal provision is impacted, modified, or influenced by another action, decision, or provision.
-
E.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
- 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_69aed96a60088190ab1df8390fffc935 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7482d708190a3ec74745b102a4c |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:16 p.m.