Triple

T540487
Position Surface form Disambiguated ID Type / Status
Subject Angola E12616 entity
Predicate capital P234 FINISHED
Object Luanda E12375 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: Luanda | Statement: [Angola, capital, Luanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luanda
Context triple: [Angola, capital, Luanda]
  • A. Luanda chosen
    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.
  • B. 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.
  • C. 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.
  • D. Kinshasa
    Kinshasa is the largest city and political, economic, and cultural center of the Democratic Republic of the Congo, located along the Congo River in Central Africa.
  • E. Libreville
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4985feee481908184a39210feab95 completed March 1, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5089bce6c8190a5c4f708fb94668b completed March 2, 2026, 3:48 a.m.
Created at: March 1, 2026, 7:32 p.m.