Triple
T6736473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black River (Ohio) |
E153766
|
entity |
| Predicate | hasPollutionHistory |
P42021
|
FINISHED |
| Object | industrial 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: industrial pollution | Statement: [Black River (Ohio), hasPollutionHistory, industrial pollution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPollutionHistory Context triple: [Black River (Ohio), hasPollutionHistory, industrial pollution]
-
A.
historicallyPollutedBy
Indicates that an entity has experienced pollution in the past as a result of actions or emissions from another entity.
-
B.
historicallyPolluted
chosen
Indicates that an entity has experienced pollution in the past, even if it may not be currently polluted.
-
C.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
-
D.
hasWaterQualityHistory
Indicates that an entity is associated with a record or series of records describing changes or measurements of its water quality over time.
-
E.
hasHistoryOf
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d18369d88190a73349075462202b |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:09 p.m.