Triple
T10327332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oromo Liberation Front |
E242791
|
entity |
| Predicate | conflictPartyIn |
P375
|
FINISHED |
| Object | Ethiopian internal conflicts involving Oromo regions |
—
|
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: Ethiopian internal conflicts involving Oromo regions | Statement: [Oromo Liberation Front, conflictPartyIn, Ethiopian internal conflicts involving Oromo regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictPartyIn Context triple: [Oromo Liberation Front, conflictPartyIn, Ethiopian internal conflicts involving Oromo regions]
-
A.
conflictSide
chosen
Indicates that an entity participates as a distinct party or faction on one side of a conflict or dispute.
-
B.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
C.
hasPartOfConflict
Indicates that one conflict includes another conflict as a constituent or subordinate part of it.
-
D.
conflictCountry
Indicates that there is an armed conflict or war involving the referenced country as a participant.
-
E.
mainParties
Indicates the primary entities that are directly and centrally involved in a given relationship, event, or agreement.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ce69b881909f27d97c90643634 |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f64a648190a79980d647898eb0 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:51 a.m.