Triple
T6394872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kudryavy |
E143916
|
entity |
| Predicate | hasPersistentGasEmissions |
P70370
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kudryavy, hasPersistentGasEmissions, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPersistentGasEmissions Context triple: [Kudryavy, hasPersistentGasEmissions, true]
-
A.
emissionsControl
Indicates a relationship where one entity regulates, limits, or manages the release of emissions produced by another entity or process.
-
B.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
C.
emissionsComparedToPredecessor
Indicates how the emissions of an entity compare in magnitude (e.g., higher, lower, or equal) to those of its immediate predecessor.
-
D.
hasCarbonFootprintCategory
Indicates that an entity is associated with a specific classification of its carbon footprint level or impact.
-
E.
emissionType
Indicates the specific category or kind of emission associated with an entity or activity.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0688275d0819086b58123c743a6db |
completed | March 22, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69c060f25c088190b433f78553ff1d84 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623d23448190a75cf5d802fc0a02 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:35 p.m.