Triple

T20207280
Position Surface form Disambiguated ID Type / Status
Subject Abéché E493385 entity
Predicate roadConnection P385 FINISHED
Object N’Djamena 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: N’Djamena | Statement: [Abéché, roadConnection, N’Djamena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: N’Djamena
Context triple: [Abéché, roadConnection, 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 (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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d934f808190bbfeb96f5bf2dfb9 completed April 20, 2026, 6:16 p.m.
Created at: April 11, 2026, 11:38 p.m.