Triple
T20146192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korku |
E491308
|
entity |
| Predicate | subfamilyOf |
P1244
|
FINISHED |
| Object | Munda languages |
—
|
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: Munda languages | Statement: [Korku, subfamilyOf, Munda languages]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Munda languages Context triple: [Korku, subfamilyOf, Munda languages]
-
A.
Munda languages
chosen
Munda languages are a branch of the Austroasiatic language family spoken primarily by indigenous communities in eastern and central India.
-
B.
Thura-Yura languages
Thura-Yura languages are a group of closely related Australian Aboriginal languages traditionally spoken in parts of South Australia.
-
C.
Muna–Buton languages
The Muna–Buton languages are a subgroup of Austronesian languages spoken primarily in southeastern Sulawesi and nearby islands in Indonesia.
-
D.
Moru–Madi languages
The Moru–Madi languages are a subgroup of related Central Sudanic languages spoken primarily in South Sudan, Uganda, and the Democratic Republic of the Congo.
-
E.
Tebu languages
The Tebu languages are a group of closely related Saharan languages spoken primarily by the Tebu people across parts of Chad, Niger, and Libya.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679e43a48190b3a5da5710b07ff7 |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.