Triple

T21512395
Position Surface form Disambiguated ID Type / Status
Subject Niger Basin Authority E530759 entity
Predicate memberState P10 FINISHED
Object Benin 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: Benin | Statement: [Niger Basin Authority, memberState, Benin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benin
Context triple: [Niger Basin Authority, memberState, Benin]
  • A. Benin chosen
    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.
  • B. Togo
    Togo is a 2019 historical adventure drama film that tells the true story of a sled dog and his musher leading a perilous serum run across Alaska.
  • C. Togo
    Togo is a small village in eastern Saskatchewan, Canada, known for its rural prairie setting and agricultural community.
  • D. Togo
    Togo is a small West African country on the Gulf of Guinea, known for its diverse cultures, coastal capital Lomé, and history as a former French colony.
  • E. Côte d'Ivoire
    Côte d'Ivoire is a West African country on the Gulf of Guinea known for its cocoa production, diverse cultures, and economic prominence in the region.
  • 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea8779c081908171c58d345d54ae completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:25 p.m.