Triple
T7410402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingston Fossil Plant |
E170986
|
entity |
| Predicate | disasterEnvironmentalImpact |
P73800
|
FINISHED |
| Object | contamination of Emory River |
—
|
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: contamination of Emory River | Statement: [Kingston Fossil Plant, disasterEnvironmentalImpact, contamination of Emory River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disasterEnvironmentalImpact Context triple: [Kingston Fossil Plant, disasterEnvironmentalImpact, contamination of Emory River]
-
A.
causeOfDisaster
chosen
Indicates that the subject is responsible for bringing about or triggering the specified disaster.
-
B.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
C.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
D.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
E.
environmentalEvent
Indicates an occurrence or phenomenon related to the natural environment, such as climatic, ecological, or geophysical changes or incidents.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f29ebea48190be96c6bc1e6406fb |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f0323b2c819098ab72c33e6d8534 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.