Triple
T19613680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nembe Local Government Area |
E470800
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Nembe 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: Nembe language | Statement: [Nembe Local Government Area, hasLanguage, Nembe language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nembe language Context triple: [Nembe Local Government Area, hasLanguage, Nembe language]
-
A.
Nembe language
chosen
The Nembe language is an Ijoid language spoken primarily by the Nembe people in Bayelsa State in Nigeria’s Niger Delta region.
-
B.
Nyemba language
The Nyemba language is a Bantu language spoken primarily by the Nyemba (Nyaneka-Nkhumbi) people of southwestern Angola.
-
C.
Tanema language
Tanema is a nearly extinct Oceanic language once spoken on Vanikoro Island in the Temotu Province of the Solomon Islands.
-
D.
Kumbewaha language
The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
-
E.
Nambya language
Nambya is a Bantu language spoken primarily in northwestern Zimbabwe and northeastern Botswana, closely related to Kalanga and used by the Nambya people.
- 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640cd5de48190a9f7bab4da3f5b5a |
completed | April 20, 2026, 3:05 p.m. |
Created at: April 10, 2026, 1:43 p.m.