Triple
T25275084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Nations |
E633672
|
entity |
| Predicate | hasRegionalPresenceIn |
P32293
|
FINISHED |
| Object | Africa |
—
|
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: Africa | Statement: [United Nations, hasRegionalPresenceIn, Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalPresenceIn Context triple: [United Nations, hasRegionalPresenceIn, Africa]
-
A.
hasRegionStrongPresence
chosen
Indicates that an entity maintains a significant, influential, or concentrated presence within a specified region.
-
B.
hasRegionalEntity
Indicates that one entity includes, governs, or is associated with another entity that functions as its regional subdivision or component.
-
C.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
D.
hasRegionalServices
Indicates that an entity provides or is associated with services that operate within a specific geographic region or set of regions.
-
E.
hasOverseasPresenceIn
Indicates that an entity maintains operations, offices, or activities in a foreign country or region.
- 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_69e75a92f48881909974ff9c11150a2e |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 21, 2026, 1:17 p.m.