Triple
T32491119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurya people |
E830386
|
entity |
| Predicate | borderlandGroup |
P191962
|
FINISHED |
| Object | Kenya–Tanzania border communities |
—
|
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: Kenya–Tanzania border communities | Statement: [Kurya people, borderlandGroup, Kenya–Tanzania border communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderlandGroup Context triple: [Kurya people, borderlandGroup, Kenya–Tanzania border communities]
-
A.
borderStreet
Indicates that a street forms or lies along the boundary between two geographic areas or properties.
-
B.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
C.
borderCountrySide
Indicates that one country shares a land border with the side or region of another country.
-
D.
borderRegime
Indicates the type, rules, or control system governing how movement or interaction is managed across a border between entities.
-
E.
borderCultureWith
chosen
Indicates that two regions or entities share a common boundary across which cultural traits, practices, or influences are actively exchanged or intertwined.
- 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff0b6bc4a88190bf1d38c6ea26bcdc |
completed | May 9, 2026, 10:24 a.m. |
| PD | Predicate disambiguation | batch_69ff082a22f4819095ded971dbd8ea7b |
completed | May 9, 2026, 10:10 a.m. |
Created at: May 1, 2026, 12:59 a.m.