Triple

T14645308
Position Surface form Disambiguated ID Type / Status
Subject Mansa Musa E343830 entity
Predicate alsoKnownAs P39 FINISHED
Object Mali Musa E1113801 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: Mali Musa | Statement: [Mansa Musa, alsoKnownAs, Mali Musa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mali Musa
Context triple: [Mansa Musa, alsoKnownAs, Mali Musa]
  • A. Mahamudu
    Mahamudu is the given name of Mahamudu Bawumia, a prominent Ghanaian economist and politician who has served as Vice President of Ghana.
  • B. Moussa Mara
    Moussa Mara is a Malian politician who served as Prime Minister of Mali and has been active in public administration and governance reform.
  • C. Kankan Musa chosen
    Kankan Musa is another name for Mansa Musa, the 14th-century emperor of the Mali Empire renowned for his immense wealth and lavish pilgrimage to Mecca.
  • D. Si Moussa
    Si Moussa was a powerful 19th-century grand vizier of Morocco who served under Sultan Hassan I and commissioned the opulent Bahia Palace in Marrakech.
  • E. Moussa
    Moussa is the protagonist of the work "Child of Fortune," around whom the story’s central events and character development revolve.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4ea6d8481908e6331ca173c646b completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf07acd748190b2821dee21ecd740 completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:26 a.m.