Triple
T24761938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swansea copper industry |
E619469
|
entity |
| Predicate | importedRawMaterialFrom |
P46598
|
FINISHED |
| Object | North America |
—
|
NE NERFINISHED |
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: North America | Statement: [Swansea copper industry, importedRawMaterialFrom, North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: importedRawMaterialFrom Context triple: [Swansea copper industry, importedRawMaterialFrom, North America]
-
A.
importedCommodity
chosen
Indicates that a commodity has been brought into a country or region from abroad through import activities.
-
B.
imported
Indicates that something was brought into a country, system, or context from an external source.
-
C.
importedWith
Indicates that one entity was brought into a system, context, or location together with or as part of another entity during an import process.
-
D.
hasMaterialImport
Indicates that one entity has another entity as a significant or primary material used in its composition or production.
-
E.
originalMaterialFor
Indicates that one entity serves as the source or basis material from which another entity is derived, adapted, or created.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 4:27 a.m.