Triple
T8496990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BSF Water Wing |
E201123
|
entity |
| Predicate | typeOfBorderGuarding |
P14206
|
FINISHED |
| Object | water border guarding |
—
|
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: water border guarding | Statement: [BSF Water Wing, typeOfBorderGuarding, water border guarding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfBorderGuarding Context triple: [BSF Water Wing, typeOfBorderGuarding, water border guarding]
-
A.
hasBorderGuardingMandateWith
Indicates that one entity has an official responsibility or mandate to guard, monitor, or secure a border in cooperation or association with another entity.
-
B.
hasBorderFacilityType
chosen
Indicates that a border facility possesses or is classified by a specific type or category of border-related infrastructure or service.
-
C.
hadBorderType
Indicates that a boundary between two entities existed and specifies the nature or classification of that border (e.g., land, maritime, disputed).
-
D.
countryBorderType
Indicates the type or nature of the border relationship that exists between two countries.
-
E.
numberOfBorderGuards
Indicates the quantity of border guards associated with a given location, event, or entity.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe57f8c508190b3a93ef180db9873 |
completed | March 31, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cbd10a4b0881909e254117780dc823 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:13 p.m.