Triple
T7823956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afghan Public Protection Force |
E181198
|
entity |
| Predicate | hasArmedPersonnel |
P34265
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Afghan Public Protection Force, hasArmedPersonnel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArmedPersonnel Context triple: [Afghan Public Protection Force, hasArmedPersonnel, true]
-
A.
hasSecurityTeam
Indicates that an entity is supported or protected by a designated security team responsible for its safety or security operations.
-
B.
hasMilitaryPresence
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
C.
hasSergeantAtArms
Indicates that an organization, body, or group is associated with and formally appoints a specific individual to serve in the role of Sergeant-at-Arms.
-
D.
hasEmbarkedPersonnel
Indicates that one entity has taken personnel on board or loaded them for transport or deployment.
-
E.
armed
chosen
Indicates that an entity is equipped with or carrying a weapon or weapons.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cafa0abff08190b0245ceca5f20cae |
completed | March 30, 2026, 10:32 p.m. |
| PD | Predicate disambiguation | batch_69cae91ae008819098e56bbe51143b31 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:42 p.m.