Triple
T6978704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onondaga Lake |
E161780
|
entity |
| Predicate | pollutants |
P29039
|
FINISHED |
| Object | mercury contamination |
—
|
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: mercury contamination | Statement: [Onondaga Lake, pollutants, mercury contamination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pollutants Context triple: [Onondaga Lake, pollutants, mercury contamination]
-
A.
pollutant
Indicates that one entity is a substance or factor that contaminates or degrades the quality of another entity or environment.
-
B.
pollutantsCovered
Indicates that certain pollutants are included within the scope, protection, regulation, or consideration defined by a particular entity, policy, or agreement.
-
C.
targetPollutant
chosen
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
D.
pollutionSource
Indicates that one entity is the origin or cause of pollution affecting another entity or environment.
-
E.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db6aa6188190af7656ff4d0e3230 |
completed | March 27, 2026, 7:32 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.