Triple

T12587922
Position Surface form Disambiguated ID Type / Status
Subject Sulley Muntari E300516 entity
Predicate placeOfBirth P1 FINISHED
Object Konongo E561830 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: Konongo | Statement: [Sulley Muntari, placeOfBirth, Konongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konongo
Context triple: [Sulley Muntari, placeOfBirth, Konongo]
  • A. Konongo chosen
    Konongo is a prominent mining and commercial town in central Ghana known historically for its gold deposits and later manganese production.
  • B. Kongolo
    Kongolo is a town in the Tanganyika Province of the Democratic Republic of the Congo, situated along the Lukuga River and serving as a local transport and trading hub.
  • C. Kongō
    Kongō was a Japanese Kongō-class fast battleship that served prominently in the Imperial Japanese Navy during World War II.
  • D. 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.
  • E. 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.
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954bbe72c8190aa11090bb6b480c9 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ebed164819083fbdaa775a59cd4 completed May 2, 2026, 8:29 p.m.
Created at: April 9, 2026, 5:05 p.m.