Triple
T654946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Nyangani |
E11626
|
entity |
| Predicate | countryBorderProximity |
P17986
|
FINISHED |
| Object | near Mozambique 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: near Mozambique border | Statement: [Mount Nyangani, countryBorderProximity, near Mozambique border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryBorderProximity Context triple: [Mount Nyangani, countryBorderProximity, near Mozambique border]
-
A.
countryBordering
Indicates that one country shares a land or maritime boundary directly with another country.
-
B.
borderedBy
Indicates that one entity shares a common boundary or edge with another entity.
-
C.
continentBorders
Indicates that one continent shares a land or maritime boundary directly with another continent.
-
D.
neighboringCountryBySea
Indicates that one country is adjacent to another with their territories touching via a shared sea boundary rather than solely by land.
-
E.
borderedByContinent
Indicates that one entity has a land or maritime boundary directly adjacent to the specified continent.
- F. None of above. chosen
Provenance (4 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f4d57688190a9515ac494a97b22 |
completed | March 1, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69a49d121cec81909986c91291bb4ca8 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49ee356c0819085e2e82831cf1360 |
completed | March 1, 2026, 8:17 p.m. |
Created at: March 1, 2026, 7:36 p.m.