Triple
T13655314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Sudan |
E326844
|
entity |
| Predicate | borderConflictHistory |
P49394
|
FINISHED |
| Object | marginalization grievances |
—
|
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: marginalization grievances | Statement: [Eastern Sudan, borderConflictHistory, marginalization grievances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderConflictHistory Context triple: [Eastern Sudan, borderConflictHistory, marginalization grievances]
-
A.
conflictHistory
Indicates a history of conflict or antagonistic interactions that have occurred between the related entities.
-
B.
borderHistory
Indicates the historical changes, events, or status of borders between entities over time.
-
C.
conflictCountry
Indicates that there is an armed conflict or war involving the referenced country as a participant.
-
D.
opponentInHistoricalConflict
Indicates that two entities stood on opposing sides in a specific historical conflict or war.
-
E.
borderDisputesWith
chosen
Indicates that there are contested or unresolved boundary claims between two 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60ace048190a4b92310ba272bd1 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.