Triple

T480487
Position Surface form Disambiguated ID Type / Status
Subject Fulani E9155 entity
Predicate presentInCountry P7827 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: [Fulani, presentInCountry, Nigeria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nigeria
Context triple: [Fulani, presentInCountry, 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f057c4ac819080cf43ffaa56c350 completed Feb. 28, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5089817248190b53d78e5b937026b completed March 2, 2026, 3:48 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.