Triple
T4431903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Sumatra |
E95349
|
entity |
| Predicate | hasLocalLanguage |
P4185
|
FINISHED |
| Object | Musi language |
E397039
|
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: Musi language | Statement: [South Sumatra, hasLocalLanguage, Musi language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Musi language Context triple: [South Sumatra, hasLocalLanguage, Musi language]
-
A.
Musi language
chosen
Musi language is an Austronesian language spoken primarily in South Sumatra, Indonesia, especially around the city of Palembang and along the Musi River.
-
B.
Moru language
The Moru language is a Central Sudanic language spoken primarily by the Moru people of South Sudan.
-
C.
Mumuye language
The Mumuye language is a Niger-Congo language spoken primarily by the Mumuye people in northeastern Nigeria.
-
D.
Muna language
The Muna language is an Austronesian language spoken primarily on Muna Island in Southeast Sulawesi, Indonesia, known for its rich verbal morphology and distinct phonological system.
-
E.
Mambae language
The Mambae language is an Austronesian language spoken primarily in East Timor, notable for its role in local identity and traditional culture.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3556cd83881908547aa311c4f17fa |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6137171148190b77a6f783d5cf315 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:31 p.m.