Triple
T22933512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butonese Wolio |
E569509
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Busoa 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: Busoa language | Statement: [Butonese Wolio, closelyRelatedTo, Busoa language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Busoa language Context triple: [Butonese Wolio, closelyRelatedTo, Busoa language]
-
A.
Busoa language
chosen
The Busoa language is an Austronesian language spoken by a small community in Southeast Sulawesi, Indonesia.
-
B.
Agutaynen language
Agutaynen is an Austronesian language spoken by the Agutaynen people of Palawan in the Philippines.
-
C.
Lotuko language
The Lotuko language is an Eastern Nilotic language spoken primarily by the Lotuko people of South Sudan.
-
D.
Nomatsiguenga language
The Nomatsiguenga language is an Arawakan language spoken by the Nomatsiguenga people of Peru’s Amazon rainforest, closely associated with the broader Asháninka linguistic and cultural group.
-
E.
Bafia language
The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
- 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_69e2458f7d008190901dccbaebeaba24 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181337ff881909d90cf3f5bae7516 |
completed | April 29, 2026, 3:55 a.m. |
Created at: April 17, 2026, 3:44 p.m.