Triple

T12035658
Position Surface form Disambiguated ID Type / Status
Subject Marion Brown E286530 entity
Predicate notableWork P4 FINISHED
Object Porto Novo E450703 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: Porto Novo | Statement: [Marion Brown, notableWork, Porto Novo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porto Novo
Context triple: [Marion Brown, notableWork, Porto Novo]
  • A. Porto Novo chosen
    Porto Novo is the main port town and administrative center on the island of Santo Antão in Cape Verde.
  • B. Porto-Novo
    Porto-Novo is the official capital city of Benin, known for its colonial architecture and role as a political and cultural center in West Africa.
  • C. Ouidah
    Ouidah is a coastal city in Benin historically known as a major center of the transatlantic slave trade and for its rich Vodun (Voodoo) cultural heritage.
  • D. Parakou
    Parakou is a major city in central Benin that serves as an important commercial and transportation hub for the surrounding region.
  • E. Biassou
    Biassou was a prominent early leader of the Haitian Revolution, known for his role in organizing and directing the initial slave uprisings against French colonial rule.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90408cbf0819093270c9833ef149a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d7d453c8190a27c5feca8f38991 completed May 1, 2026, 12:33 p.m.
Created at: April 8, 2026, 9:47 p.m.