Triple

T6989504
Position Surface form Disambiguated ID Type / Status
Subject CEEAC E162048 entity
Predicate headquartersLocation P62 FINISHED
Object Libreville, Gabon 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, Gabon | Statement: [CEEAC, headquartersLocation, Libreville, Gabon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Libreville, Gabon
Context triple: [CEEAC, headquartersLocation, Libreville, Gabon]
  • A. Libreville chosen
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • B. Port-Gentil
    Port-Gentil is Gabon's second-largest city and a major oil and port hub located on the country's Atlantic coast.
  • C. Limbé
    Limbé is a historic town in northern Haiti known for its agricultural surroundings and role in the country’s colonial and revolutionary past.
  • D. Beni Douala
    Beni Douala is a town and commune in northern Algeria, situated in the Kabylie region within Tizi Ouzou Province.
  • E. Malabo
    Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
  • 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbbee0e881909f78370856594cd6 completed March 27, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b8b9a0e881909ee8f92ecb6fef66 completed March 28, 2026, 11:17 a.m.
Created at: March 27, 2026, 2:32 p.m.