Triple
T6511091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namibia and Botswana |
E150133
|
entity |
| Predicate | shareBorderCharacteristic |
P35564
|
FINISHED |
| Object | largely land border |
—
|
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: largely land border | Statement: [Namibia and Botswana, shareBorderCharacteristic, largely land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareBorderCharacteristic Context triple: [Namibia and Botswana, shareBorderCharacteristic, largely land border]
-
A.
sharesBorderType
chosen
Indicates that two entities are connected by a common boundary characterized by the same specified type of border (e.g., land, river, maritime).
-
B.
borderCharacteristic
Indicates that one entity specifies a property, feature, or quality of the border or boundary of another entity.
-
C.
shareNotableBorderRegion
Indicates that two entities share a common border in a region that is particularly significant or notable (e.g., historically, politically, or geographically).
-
D.
relatedBorder
Indicates that two geographic or political entities share a common boundary or border with each other.
-
E.
sharesBorderingNetworkWith
Indicates that two entities are connected through adjacent or directly neighboring positions within the same network structure.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f3ad7d081909162f1a625fc52b1 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab98c78819081743e614df04e1d |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:43 p.m.