Triple
T8365045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyamuragira |
E197105
|
entity |
| Predicate | hasLargeSO2Emissions |
P32799
|
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: [Nyamuragira, hasLargeSO2Emissions, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLargeSO2Emissions Context triple: [Nyamuragira, hasLargeSO2Emissions, true]
-
A.
hasPersistentGasEmissions
Indicates that an entity continuously or repeatedly releases gaseous substances over an extended period.
-
B.
isMajorSourceOf
chosen
Indicates that one entity serves as a primary or dominant origin, cause, or provider of another entity or effect.
-
C.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
-
D.
hasIndustrialPlant
Indicates that an entity possesses, operates, or is associated with an industrial plant facility.
-
E.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb808bc22481909ce2f8b48cc95806 |
completed | March 31, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69cb70cd04b08190ab5f72afd22a7967 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6 p.m.