Triple
T3808703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rim Fire 2013 (affected area) |
E93074
|
entity |
| Predicate | vegetationRegrowthObserved |
P51961
|
FINISHED |
| Object | post-2013 |
—
|
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: post-2013 | Statement: [Rim Fire 2013 (affected area), vegetationRegrowthObserved, post-2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vegetationRegrowthObserved Context triple: [Rim Fire 2013 (affected area), vegetationRegrowthObserved, post-2013]
-
A.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
B.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
C.
hasVegetationIssue
Indicates that an entity is affected by a problem, damage, or abnormal condition related to its vegetation or plant life.
-
D.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
-
E.
treeVigor
Indicates the overall health, strength, and growth potential of a tree based on its physiological condition and environmental factors.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:16 p.m.