Triple
T6494054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meliolales |
E148110
|
entity |
| Predicate | impactOnPlants |
P41548
|
FINISHED |
| Object | reduction of photosynthetic area |
—
|
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: reduction of photosynthetic area | Statement: [Meliolales, impactOnPlants, reduction of photosynthetic area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnPlants Context triple: [Meliolales, impactOnPlants, reduction of photosynthetic area]
-
A.
affectsPlantPart
chosen
Indicates that one entity produces an influence, change, or impact on a specific part of a plant.
-
B.
involvesPlant
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
-
C.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
D.
agriculturalImpact
Indicates the effect that an action, condition, or entity has on agricultural systems, productivity, or practices.
-
E.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
- 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab7c0b8819091437a293b40dfd2 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:53 p.m.