Triple

T12155696
Position Surface form Disambiguated ID Type / Status
Subject Senegambian languages E289568 entity
Predicate hasNotableLanguage P7390 FINISHED
Object Manjak E151358 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: Manjak | Statement: [Senegambian languages, hasNotableLanguage, Manjak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manjak
Context triple: [Senegambian languages, hasNotableLanguage, Manjak]
  • A. Manjaco chosen
    The Manjaco are an ethnic group of West Africa, primarily living in Guinea-Bissau, known for their rice cultivation, coastal settlements, and distinct language and cultural traditions.
  • B. Yakoma
    Yakoma is a Bantu language spoken by the Yakoma people primarily in the Central African Republic.
  • C. Mahinog
    Mahinog is a coastal municipality on Camiguin Island in the Philippines known for its rural communities and access to nearby islets and marine attractions.
  • D. Malindangia
    Malindangia is a genus of birds in the cuckooshrike family Campephagidae, found in parts of Southeast Asia.
  • E. Mandau
    The Mandau is a river in Central Europe that flows through the Czech Republic and Germany before joining the Lusatian Neisse.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c1673c8190830cd15525d16869 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f69c8d408190abbc900deb534045 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:50 p.m.