Triple
T21473386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandegusu |
E529788
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Simbo 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: Simbo language | Statement: [Mandegusu, hasLanguage, Simbo language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simbo language Context triple: [Mandegusu, hasLanguage, Simbo language]
-
A.
Simbo language
chosen
The Simbo language is an Oceanic language spoken on Simbo Island in the Western Province of the Solomon Islands.
-
B.
Sayawa language
The Sayawa language is a Chadic language spoken primarily by the Sayawa people in Bauchi State, northeastern Nigeria.
-
C.
Badimaya language
Badimaya language is an Australian Aboriginal language traditionally spoken by the Yamatji people of Western Australia.
-
D.
Patamona language
The Patamona language is an indigenous Cariban language spoken by the Patamona people of the Guiana Highlands in Guyana and northern Brazil.
-
E.
Bitama language
The Bitama language is a lesser-known Nilo-Saharan language spoken by a subgroup of the Kunama people in the Horn of Africa.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea156dac819087c4594d022d3df6 |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:19 p.m.