Triple
T14228783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwe–South Africa border |
E352695
|
entity |
| Predicate | hasLanguageInBorderRegion |
P54485
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Zimbabwe–South Africa border, hasLanguageInBorderRegion, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageInBorderRegion Context triple: [Zimbabwe–South Africa border, hasLanguageInBorderRegion, English]
-
A.
hasLanguageOfSurroundingCountries
chosen
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
B.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
C.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
D.
hasOfficialLanguageOfSurroundingCountry
Indicates that an entity uses as its official language the same language that is official in the country surrounding it.
-
E.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622a48508190bbfedb762bd1674d |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:07 a.m.