Triple
T37496900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Methylococcales |
E931849
|
entity |
| Predicate | impactOnClimate |
P182016
|
FINISHED |
| Object | mitigation of greenhouse gas levels |
—
|
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: mitigation of greenhouse gas levels | Statement: [Methylococcales, impactOnClimate, mitigation of greenhouse gas levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnClimate Context triple: [Methylococcales, impactOnClimate, mitigation of greenhouse gas levels]
-
A.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
B.
globalClimaticImpact
chosen
Indicates that an entity has a significant influence on climate patterns or conditions at a global scale.
-
C.
impactOnHumans
Indicates a relationship where something produces an effect, influence, or consequence on humans.
-
D.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
E.
climateConsiderations
Indicates that the action or decision takes into account environmental and climate-related factors, such as emissions, resilience, or climate impact.
- 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:17 p.m.