Triple

T11648090
Position Surface form Disambiguated ID Type / Status
Subject Malabo Lopelo Melaka E276827 entity
Predicate geographicalAssociation P3227 FINISHED
Object city of Malabo E56338 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: city of Malabo | Statement: [Malabo Lopelo Melaka, geographicalAssociation, city of Malabo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Malabo
Context triple: [Malabo Lopelo Melaka, geographicalAssociation, city of Malabo]
  • A. Malabo chosen
    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.
  • B. Limbé
    Limbé is a historic town in northern Haiti known for its agricultural surroundings and role in the country’s colonial and revolutionary past.
  • C. Port-Gentil
    Port-Gentil is Gabon's second-largest city and a major oil and port hub located on the country's Atlantic coast.
  • D. Libreville
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • E. Ouaga
    Ouaga is the commonly used short name for Ouagadougou, the capital and largest city of Burkina Faso.
  • 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a2cd9bb0819093d107204bed2fe0 completed April 10, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87f903c48190b9055ad4cfebb1e1 completed April 26, 2026, 9:47 p.m.
Created at: April 8, 2026, 9:39 p.m.