Triple
T18734550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guaire River |
E458125
|
entity |
| Predicate | typeOfPollution |
P98276
|
FINISHED |
| Object | organic pollution |
—
|
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: organic pollution | Statement: [Guaire River, typeOfPollution, organic pollution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfPollution Context triple: [Guaire River, typeOfPollution, organic pollution]
-
A.
targetPollutant
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
B.
pollutionSource
Indicates that one entity is the origin or cause of pollution affecting another entity or environment.
-
C.
pollutant
Indicates that one entity is a substance or factor that contaminates or degrades the quality of another entity or environment.
-
D.
hasPollutionIssue
chosen
Indicates that an entity is affected by, associated with, or characterized by a pollution-related problem or concern.
-
E.
pollutionTolerance
Indicates the degree to which an entity can withstand or remain unaffected by environmental pollution without adverse effects.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d7a06788190a8e09c657aaeb8e5 |
completed | April 20, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:51 a.m.