Triple

T22883908
Position Surface form Disambiguated ID Type / Status
Subject Ndé E567550 entity
Predicate largestTown P235 FINISHED
Object Bangangté 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: Bangangté | Statement: [Ndé, largestTown, Bangangté]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangangté
Context triple: [Ndé, largestTown, Bangangté]
  • A. Bangangté chosen
    Bangangté is a prominent city in western Cameroon known as an important administrative and commercial center of the West Region.
  • B. Bobangi
    Bobangi is a Bantu language historically spoken along the Congo River that served as a major regional trade lingua franca in Central Africa.
  • C. Welket Bungué
    Welket Bungué is a Bissau-Guinean-born Portuguese actor known for his work in international cinema, including prominent roles in films such as "Crimes of the Future" and "Berlin Alexanderplatz."
  • D. Bakoteh
    Bakoteh is a residential neighborhood within the urban area of Serekunda in The Gambia.
  • E. Baatombu
    Baatombu are a West African ethnic group, also known as the Bariba, primarily living in northern Benin and neighboring regions.
  • 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_69e2458a92ec81908fc1cd5f6407d2ab completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17fbfc5848190aa612ea51df5a9ec completed April 29, 2026, 3:49 a.m.
Created at: April 17, 2026, 3:39 p.m.