Triple
T21713889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinyankole language |
E535971
|
entity |
| Predicate | hasLexicalSimilarityWith |
P11829
|
FINISHED |
| Object | Rukiga 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: Rukiga language | Statement: [Kinyankole language, hasLexicalSimilarityWith, Rukiga language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rukiga language Context triple: [Kinyankole language, hasLexicalSimilarityWith, Rukiga language]
-
A.
Rukiga language
chosen
Rukiga language is a Bantu language spoken primarily by the Bakiga people in southwestern Uganda.
-
B.
Lusoga language
The Lusoga language is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
-
C.
Ngindo language
The Ngindo language is a Bantu language spoken by the Ngindo people of southeastern Tanzania.
-
D.
Kinyankole language
The Kinyankole language is a Bantu language spoken primarily by the Banyankole people in southwestern Uganda.
-
E.
Nyamwezi language
The Nyamwezi language is a Bantu language spoken primarily by the Nyamwezi people of western-central Tanzania.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5369be88190bafc10863d4d1bd7 |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 16, 2026, 6:47 p.m.