Triple
T21418032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nandom |
E528356
|
entity |
| Predicate | borderRegionInteractionWith |
P30106
|
FINISHED |
| Object | communities in Burkina Faso |
—
|
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: communities in Burkina Faso | Statement: [Nandom, borderRegionInteractionWith, communities in Burkina Faso]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderRegionInteractionWith Context triple: [Nandom, borderRegionInteractionWith, communities in Burkina Faso]
-
A.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
B.
borderRegionPresence
chosen
Indicates the presence or occurrence of something within or along a border region between areas or territories.
-
C.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
D.
borderRegime
Indicates the type, rules, or control system governing how movement or interaction is managed across a border between entities.
-
E.
borderIssue
Indicates a dispute, conflict, or problem related to the definition, control, or management of a boundary between two or more entities.
- 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_69e0c454c248819093425d1099101c09 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee62d29f948190b820c92014d1c53a |
completed | April 26, 2026, 7:09 p.m. |
| PD | Predicate disambiguation | batch_69e61633f8208190a2a849457c4e4198 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 5:46 p.m.