Triple
T28929340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro Verde copper deposit |
E733737
|
entity |
| Predicate | exploitation |
P33834
|
FINISHED |
| Object | industrial-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: industrial-scale mining | Statement: [Cerro Verde copper deposit, exploitation, industrial-scale mining]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exploitation Context triple: [Cerro Verde copper deposit, exploitation, industrial-scale mining]
-
A.
exploitedFor
Indicates that one entity is unfairly or abusively used by another entity as a resource, means, or advantage for the latter’s benefit.
-
B.
exploits
chosen
Indicates that one entity unfairly or selfishly uses another entity or resource for its own advantage or benefit.
-
C.
exploitationBegan
Indicates the point in time when the exploitation or use of a resource, person, or system was initiated.
-
D.
exploitationPossible
Indicates that one entity is in a position to unfairly use or benefit from another entity or resource, suggesting that exploitation can occur.
-
E.
isExploitedFor
Indicates that one entity is unfairly or abusively used by another entity as a resource, means, or advantage for the latter’s benefit.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f67f7efc3c8190986d2d95b7a23729 |
completed | May 2, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 28, 2026, 8:26 a.m.