Triple

T18875150
Position Surface form Disambiguated ID Type / Status
Subject Sean MacEoin E461662 entity
Predicate workLocation P7 FINISHED
Object Congo 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: Congo | Statement: [Sean MacEoin, workLocation, Congo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Congo
Context triple: [Sean MacEoin, workLocation, Congo]
  • A. Congo chosen
    Congo is a Central African country whose economy is heavily reliant on oil production and exports.
  • B. Kongō
    Kongō was a Japanese Kongō-class fast battleship that served prominently in the Imperial Japanese Navy during World War II.
  • C. 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.
  • D. Congo River
    The Congo River is Africa’s second-longest river and the world’s deepest, flowing through central Africa to the Atlantic Ocean and serving as a major waterway for transport, ecology, and regional economies.
  • E. Katanga
    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.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c3cd49748190948d535918aec3de completed April 20, 2026, 6:12 a.m.
Created at: April 10, 2026, 11:57 a.m.