Triple

T2160168
Position Surface form Disambiguated ID Type / Status
Subject Prime Minister of Gabon E47981 entity
Predicate seat P75 FINISHED
Object Libreville E47980 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: Libreville | Statement: [Prime Minister of Gabon, seat, Libreville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Libreville
Context triple: [Prime Minister of Gabon, seat, Libreville]
  • A. Libreville chosen
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • B. Douala
    Douala is the economic capital and main port city of Cameroon, located on the Wouri River along the Atlantic coast.
  • C. Yaoundé
    Yaoundé is the political and administrative center of Cameroon, known for its hilly terrain and role as a major cultural and economic hub in Central Africa.
  • D. Abidjan
    Abidjan is a major economic and cultural hub on the southern coast of Côte d'Ivoire, known for its bustling port, modern skyline, and status as one of the largest cities in West Africa.
  • E. Brazzaville
    Brazzaville is the capital and largest city of the Republic of the Congo, located on the Congo River directly across from Kinshasa in Central Africa.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe8894d481908eda9363fd36fea6 completed March 7, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6538c750819093d2e3f8e5f66a63 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:45 p.m.