Triple
T7822200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quetta Cantonment |
E181157
|
entity |
| Predicate | militaryPresenceType |
P14275
|
FINISHED |
| Object | permanent garrison |
—
|
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: permanent garrison | Statement: [Quetta Cantonment, militaryPresenceType, permanent garrison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryPresenceType Context triple: [Quetta Cantonment, militaryPresenceType, permanent garrison]
-
A.
hasMilitaryPresence
chosen
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
B.
militaryInstallationType
Indicates the specific category or kind of military installation associated with an entity (e.g., base, fort, airfield, naval station).
-
C.
militaryBasis
Indicates that one entity serves as the foundational military justification, rationale, or underlying military reason for another entity or action.
-
D.
nearMilitaryInstallation
Indicates that one entity is located in close physical proximity to a military installation or facility.
-
E.
militaryActivity
Indicates that an entity is engaged in, associated with, or affected by actions, operations, or preparations conducted by armed forces.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cafa095d7081908b3e492ce58b5d5f |
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, 4:41 p.m.