Triple
T26188825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bethanie |
E654906
|
entity |
| Predicate | borderingCountryOfNation |
P4999
|
FINISHED |
| Object | South Africa |
—
|
NE NERFINISHED |
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: South Africa | Statement: [Bethanie, borderingCountryOfNation, South Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderingCountryOfNation Context triple: [Bethanie, borderingCountryOfNation, South Africa]
-
A.
borderingCountryOfState
Indicates that one country shares a land or maritime boundary directly with the specified state.
-
B.
countryBordering
chosen
Indicates that one country shares a land or maritime boundary directly with another country.
-
C.
borderingCountryOfRegion
Indicates that a country shares a land or maritime border with a specified geographic region.
-
D.
countryBorderRelation
Indicates that two countries share a common land or maritime boundary with each other.
-
E.
borderingCountryNearby
Indicates that one country is geographically close to, but does not necessarily share a direct land border with, another country.
- 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_69ee5b469bc081908fe486453fdad810 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 26, 2026, 8:43 p.m.