Triple

T23521311
Position Surface form Disambiguated ID Type / Status
Subject North East Region E574513 entity
Predicate borders P224 FINISHED
Object Togo 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: Togo | Statement: [North East Region, borders, Togo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Togo
Context triple: [North East Region, borders, Togo]
  • A. 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.
  • B. Togo chosen
    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.
  • C. Togo
    Togo is a small village in eastern Saskatchewan, Canada, known for its rural prairie setting and agricultural community.
  • D. 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.
  • E. Burkina Faso
    Burkina Faso is a landlocked West African country known for its diverse cultures, Sahelian landscapes, and capital city, Ouagadougou.
  • 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_69e245bb3dcc8190ba9a2b35972b58d0 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1aa873ad48190a86807bd4f26df82 completed April 29, 2026, 6:51 a.m.
Created at: April 17, 2026, 6:08 p.m.