Triple

T7923621
Position Surface form Disambiguated ID Type / Status
Subject Luba E184004 entity
Predicate hasNearbySettlement P4647 FINISHED
Object 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: Malabo | Statement: [Luba, hasNearbySettlement, Malabo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malabo
Context triple: [Luba, hasNearbySettlement, 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. Luanda
    Luanda is the capital and largest city of Angola, a major Atlantic port and economic hub with a history shaped by Portuguese colonial rule and the transatlantic slave trade.
  • C. Ouaga
    Ouaga is the commonly used short name for Ouagadougou, the capital and largest city of Burkina Faso.
  • D. Brazzaville
    Brazzaville is the capital and largest city of the Republic of the Congo, located on the Congo River directly across from Kinshasa in Central Africa.
  • E. Pointe-Noire
    Pointe-Noire is a major port city on the Atlantic coast of the Republic of the Congo and one of the country’s principal economic and industrial centers.
  • 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_69ca828fe7bc819090f52c88dcd72183 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aac02bc8190b13fc354a4fa91d3 completed March 31, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccec781ac88190b52305beaa213415 completed April 1, 2026, 9:59 a.m.
Created at: March 30, 2026, 5:06 p.m.