Triple
T21713888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinyankole language |
E535971
|
entity |
| Predicate | hasLexicalSimilarityWith |
P11829
|
FINISHED |
| Object | Runyoro 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: Runyoro language | Statement: [Kinyankole language, hasLexicalSimilarityWith, Runyoro language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Runyoro language Context triple: [Kinyankole language, hasLexicalSimilarityWith, Runyoro language]
-
A.
Runyoro
Runyoro is a Bantu language spoken primarily by the Banyoro people in western Uganda.
-
B.
Nyaturu language
The Nyaturu language is a Bantu language spoken primarily by the Nyaturu people in central Tanzania.
-
C.
Lusoga language
The Lusoga language is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
-
D.
Nyoro language
chosen
The Nyoro language is a Bantu language spoken primarily by the Banyoro people in western Uganda.
-
E.
Nyunga language
The Nyunga language is an Australian Aboriginal language traditionally spoken by the Noongar people of southwestern Western Australia and is part of the broader Pama–Nyungan language family.
- 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.