Triple

T5221285
Position Surface form Disambiguated ID Type / Status
Subject Swahili Coast E117874 entity
Predicate majorCity P316 FINISHED
Object Zanzibar City E122501 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: Zanzibar City | Statement: [Swahili Coast, majorCity, Zanzibar City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zanzibar City
Context triple: [Swahili Coast, majorCity, Zanzibar City]
  • A. Zanzibar City chosen
    Zanzibar City is the historic and administrative capital of Zanzibar, Tanzania, renowned for its UNESCO-listed Stone Town and rich Swahili, Arab, and colonial heritage.
  • B. Dar es Salaam
    Dar es Salaam is a major coastal metropolis on the Indian Ocean and the principal economic and commercial hub of Tanzania.
  • C. Mombasa
    Mombasa is a major coastal city in Kenya known as a key regional port and historic trading hub on the Indian Ocean.
  • D. Moshi
    Moshi is a Tanzanian town in the Kilimanjaro Region that serves as a major gateway and base for climbers ascending Mount Kilimanjaro.
  • E. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • 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_69bd4465e03081909bfcfd7113062590 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7aba05b48190b6a7fc52ab3532f0 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef8059c808190aac709a199541ce7 completed March 21, 2026, 7:56 p.m.
Created at: March 20, 2026, 1:48 p.m.