Triple

T14717694
Position Surface form Disambiguated ID Type / Status
Subject Panafrican Film and Television Festival of Ouagadougou E345726 entity
Predicate location P40 FINISHED
Object Ouagadougou E69602 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: Ouagadougou | Statement: [Panafrican Film and Television Festival of Ouagadougou, location, Ouagadougou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ouagadougou
Context triple: [Panafrican Film and Television Festival of Ouagadougou, location, Ouagadougou]
  • A. Ouagadougou chosen
    Ouagadougou is the capital and largest city of Burkina Faso, serving as its political, economic, and cultural center in the Sahel region.
  • B. Bamako
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • C. Yamoussoukro
    Yamoussoukro is the political capital of Côte d'Ivoire, known for its grand basilica and role as an administrative center in the French-speaking world.
  • D. Koudougou
    Koudougou is a major city in central Burkina Faso known as an important commercial and transportation hub.
  • E. Bobo-Dioulasso
    Bobo-Dioulasso is the second-largest city of Burkina Faso, known as a major economic and cultural center in the country’s southwest.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb98688f48190b2b19ce7aa06a6db completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c2a938081909ccd9fe7c5021dc6 completed May 9, 2026, 3 p.m.
Created at: April 10, 2026, 1:29 a.m.