Triple
T25377834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regional Mechanisms for Conflict Prevention, Management and Resolution |
E633100
|
entity |
| Predicate | aimsTo |
P79
|
FINISHED |
| Object | strengthen coordination between regional economic communities and African Union |
—
|
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: strengthen coordination between regional economic communities and African Union | Statement: [Regional Mechanisms for Conflict Prevention, Management and Resolution, aimsTo, strengthen coordination between regional economic communities and African Union]
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_69e75a90c0dc819092f928b6ea0ecc72 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f55e5d7e2c8190937af482e50e6cad |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 21, 2026, 1:38 p.m.