Triple
T15786798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puntland–Somaliland conflict |
E382756
|
entity |
| Predicate | typeOfMilitaryEngagement |
P1403
|
FINISHED |
| Object | small-arms battles |
—
|
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: small-arms battles | Statement: [Puntland–Somaliland conflict, typeOfMilitaryEngagement, small-arms battles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfMilitaryEngagement Context triple: [Puntland–Somaliland conflict, typeOfMilitaryEngagement, small-arms battles]
-
A.
warfareType
chosen
Indicates the specific kind or category of warfare that characterizes a given conflict or military engagement.
-
B.
navalEngagementType
Indicates the specific kind or category of naval combat or maritime military engagement involved in the relationship.
-
C.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
D.
opposedWarfareType
Indicates that one entity is in opposition to, or acts against, the type or form of warfare represented by the other entity.
-
E.
battleInvolvedIn
Indicates that an entity participated as a combatant or directly took part in a specific battle or military engagement.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0540380448190a025338f0e62e6d1 |
completed | April 16, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.