Triple
T30196543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sila Region |
E767645
|
entity |
| Predicate | nearBorderConflictZone |
P152442
|
FINISHED |
| Object | Darfur region of Sudan |
—
|
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: Darfur region of Sudan | Statement: [Sila Region, nearBorderConflictZone, Darfur region of Sudan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearBorderConflictZone Context triple: [Sila Region, nearBorderConflictZone, Darfur region of Sudan]
-
A.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
B.
hasBorderConflictWith
chosen
Indicates a relationship where two entities share a disputed boundary or are involved in an ongoing or historical conflict over their common border.
-
C.
nearInternationalBoundary
Indicates that one entity is located close to an international boundary separating two or more countries.
-
D.
nearStateBorderWith
Indicates that one entity is located close to the state border shared with another specified state or region.
-
E.
nearFormerBorderWith
Indicates that one entity is located close to where the former border or boundary with another entity used to be.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: April 29, 2026, 7:29 p.m.