Triple
T10094873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Abra |
E215838
|
entity |
| Predicate | hasEnvironmentalImpactType |
P92405
|
FINISHED |
| Object | large-scale mining |
—
|
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: large-scale mining | Statement: [El Abra, hasEnvironmentalImpactType, large-scale mining]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnvironmentalImpactType Context triple: [El Abra, hasEnvironmentalImpactType, large-scale mining]
-
A.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
B.
hasEnvironmentalImpactAssessment
Indicates that an entity is associated with, or subject to, an environmental impact assessment evaluating its potential effects on the environment.
-
C.
hasCarbonFootprintCategory
Indicates that an entity is associated with a specific classification of its carbon footprint level or impact.
-
D.
hasEnvironmentalRisk
Indicates that an entity poses, contributes to, or is associated with potential harm or adverse impact on the environment.
-
E.
hasEnvironmentalMitigation
Indicates that an entity has associated measures, actions, or features intended to reduce, offset, or manage its negative environmental impacts.
- F. None of above. chosen
Provenance (4 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd0784c288190967d143beca32c4b |
completed | April 2, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd5150ae98819086c4f822114b4e2c |
completed | April 1, 2026, 5:09 p.m. |
Created at: March 30, 2026, 9:02 p.m.