Triple
T16351349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakh languages |
E397067
|
entity |
| Predicate | hasSubgroup |
P747
|
FINISHED |
| Object | Batsbi language |
E1208650
|
NE 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: Batsbi language | Statement: [Nakh languages, hasSubgroup, Batsbi language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Batsbi language Context triple: [Nakh languages, hasSubgroup, Batsbi language]
-
A.
Batsbi language
chosen
The Batsbi language is a highly endangered Nakh language spoken by the Bats people in northeastern Georgia, notable for its complex grammar and small speaker community.
-
B.
Bafia language
The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
-
C.
Baatonum language
The Baatonum language is a Gur language spoken primarily by the Bariba people of Benin and neighboring areas of West Africa.
-
D.
Batuley language
The Batuley language is an Austronesian language spoken by a small community in Indonesia’s Aru Islands.
-
E.
Biwat language
The Biwat language is a Ramu family Papuan language spoken by the Biwat (Mundugumor) people of Papua New Guinea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2facb37d0819093fe45446f1e79c1 |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00355a7fb481908ed33a86c880fd49 |
completed | May 10, 2026, 7:35 a.m. |
Created at: April 10, 2026, 5:07 a.m.