Triple

T8782868
Position Surface form Disambiguated ID Type / Status
Subject Islam in Lake Chad region E208973 entity
Predicate associatedWithCity P1481 FINISHED
Object N’Djamena E113463 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: N’Djamena | Statement: [Islam in Lake Chad region, associatedWithCity, N’Djamena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: N’Djamena
Context triple: [Islam in Lake Chad region, associatedWithCity, N’Djamena]
  • A. N'Djamena chosen
    N'Djamena is the largest city and political, economic, and cultural center of Chad, located in the southwestern part of the country near the border with Cameroon.
  • B. Moundou
    Moundou is a major city in southwestern Chad and an important industrial and commercial center, particularly known for its cotton and oil industries.
  • C. Abéché
    Abéché is a major city in eastern Chad that serves as an important regional trade and administrative center.
  • D. Ouaga
    Ouaga is the commonly used short name for Ouagadougou, the capital and largest city of Burkina Faso.
  • E. Bangui
    Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural center.
  • 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f7155b081908891e84b704f0ebf completed March 31, 2026, 11:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf890077a881908ebddefc36b978d1 completed April 3, 2026, 9:31 a.m.
Created at: March 30, 2026, 6:42 p.m.