Triple

T11349246
Position Surface form Disambiguated ID Type / Status
Subject Mai-Mai militias E268798 entity
Predicate locatedIn P40 FINISHED
Object Katanga E729364 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: Katanga | Statement: [Mai-Mai militias, locatedIn, Katanga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katanga
Context triple: [Mai-Mai militias, locatedIn, Katanga]
  • A. Katanga chosen
    Katanga is a mineral-rich region in the southeastern part of the Democratic Republic of the Congo, historically known for its attempted secession in the early 1960s and significant role in the country’s political conflicts.
  • B. Kongo
    Kongo refers to the Central African ethnic and cultural group and historical kingdom whose traditions and beliefs have significantly influenced Afro-diasporic religions in the Americas.
  • C. Kongō
    Kongō was a Japanese Kongō-class fast battleship that served prominently in the Imperial Japanese Navy during World War II.
  • D. Congo
    Congo is a Central African country whose economy is heavily reliant on oil production and exports.
  • E. Luba-Kasai
    Luba-Kasai is a Bantu language spoken primarily in the Kasai region of the Democratic Republic of the Congo by the Luba people.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea23391c819089e8f9725cb3a0ff completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5438d7b58819093cc1407fefe8ab5 completed April 19, 2026, 9:05 p.m.
Created at: April 8, 2026, 9:33 p.m.