Triple

T17093503
Position Surface form Disambiguated ID Type / Status
Subject Guinean Ministry of Health E414781 entity
Predicate locatedIn P40 FINISHED
Object Conakry E69995 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: Conakry | Statement: [Guinean Ministry of Health, locatedIn, Conakry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Conakry
Context triple: [Guinean Ministry of Health, locatedIn, Conakry]
  • A. Conakry chosen
    Conakry is the capital and largest city of Guinea, serving as its main economic, cultural, and administrative center on the Atlantic coast of West Africa.
  • B. Navrongo
    Navrongo is a town in northern Ghana known as a key administrative and commercial center near the border with Burkina Faso.
  • C. Bamako
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • D. Daloa
    Daloa is a major inland city in western Côte d'Ivoire known as an important commercial and agricultural center, particularly for cocoa production.
  • E. 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.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbfb89348190942984037bd3bd2e completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139fa0a288190af69201ec88ec3c6 completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:35 a.m.