Triple
T38442729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suba people |
E906541
|
entity |
| Predicate | hasBilingualismWith |
P103278
|
FINISHED |
| Object | Luo language |
—
|
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: Luo language | Statement: [Suba people, hasBilingualismWith, Luo language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBilingualismWith Context triple: [Suba people, hasBilingualismWith, Luo language]
-
A.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
B.
bilingualismWith
chosen
Indicates a relationship where an entity possesses or is associated with the ability to use two specified languages.
-
C.
usesHeritageLanguageAlongside
Indicates that an entity communicates or operates using a heritage language in combination with one or more other languages at the same time or in the same context.
-
D.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
E.
usesBilingualInstruction
Indicates that an entity employs two languages as the medium of instruction within an educational or communicative context.
- 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_69f76e72878c8190a692836c8b01b58b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:31 p.m.