Triple
T340780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hausa |
E6832
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Nigeria |
E2050
|
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: Nigeria | Statement: [Hausa, spokenIn, Nigeria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nigeria Context triple: [Hausa, spokenIn, Nigeria]
-
A.
Nigeria
chosen
Nigeria is a populous West African country known for its diverse ethnic groups, rich cultural heritage, and status as Africa’s largest economy and oil producer.
-
B.
Cameroon
Cameroon is a Central African country known for its cultural and linguistic diversity, varied geography from coast to rainforest and savanna, and a mixed French-English colonial heritage.
-
C.
Benin
Benin is a West African country on the Gulf of Guinea known for its historical Kingdom of Dahomey and as a key region in the transatlantic slave trade.
-
D.
Ghana
Ghana is a West African nation known for being the first sub-Saharan African country to gain independence from colonial rule and for its stable democracy and rich cultural heritage.
-
E.
Niger
Niger is a landlocked West African country in the Sahel region, known for its vast desert landscapes, uranium resources, and predominantly rural population.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae611f88190955fbebe2b01835b |
completed | Feb. 28, 2026, 1:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4528ce1b88190b4f14cadd58f8001 |
completed | March 1, 2026, 2:51 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.