Triple
T8204605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FAR |
E191657
|
entity |
| Predicate | greenhouseGasesConsidered |
P81488
|
FINISHED |
| Object | carbon dioxide |
—
|
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: carbon dioxide | Statement: [FAR, greenhouseGasesConsidered, carbon dioxide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: greenhouseGasesConsidered Context triple: [FAR, greenhouseGasesConsidered, carbon dioxide]
-
A.
hasGreenhouseEffect
Indicates that one entity causes or contributes to a greenhouse effect on another entity, typically by trapping heat through atmospheric or environmental mechanisms.
-
B.
hasPersistentGasEmissions
Indicates that an entity continuously or repeatedly releases gaseous substances over an extended period.
-
C.
hasGreenhouse
Indicates that an entity possesses or includes a greenhouse structure or facility.
-
D.
hasCarbonFootprintCategory
Indicates that an entity is associated with a specific classification of its carbon footprint level or impact.
-
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. 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb7268e2dc8190b630ea2bb75d0474 |
completed | March 31, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_69cb36ad01ac81909609b15f6a6c8581 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb4ab5162c8190bddd696078689895 |
completed | March 31, 2026, 4:16 a.m. |
Created at: March 30, 2026, 5:43 p.m.