Triple
T11331774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plumtree Border Post |
E268358
|
entity |
| Predicate | transportCorridor |
P3034
|
FINISHED |
| Object | regional north–south trade routes in Southern Africa |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: regional north–south trade routes in Southern Africa | Statement: [Plumtree Border Post, transportCorridor, regional north–south trade routes in Southern Africa]
Provenance (2 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9fd38308190a5458be1bfcc89ea |
completed | April 9, 2026, 6:03 p.m. |
Created at: April 8, 2026, 9:32 p.m.