Triple

T7492709
Position Surface form Disambiguated ID Type / Status
Subject Central Line railway E177043 entity
Predicate startPoint P389 FINISHED
Object Dar es Salaam E108100 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: Dar es Salaam | Statement: [Central Line railway, startPoint, Dar es Salaam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dar es Salaam
Context triple: [Central Line railway, startPoint, Dar es Salaam]
  • A. Dar es Salaam chosen
    Dar es Salaam is a major coastal metropolis on the Indian Ocean and the principal economic and commercial hub of Tanzania.
  • B. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • C. Zanzibar City
    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.
  • D. Mombasa
    Mombasa is a major coastal city in Kenya known as a key regional port and historic trading hub on the Indian Ocean.
  • E. Arusha, Tanzania
    Arusha, Tanzania is a major city in northern Tanzania known as a diplomatic hub and gateway to popular safari destinations and Mount Kilimanjaro.
  • 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_69c69f2583808190bd1a4936c42a5815 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5784c908190b701959daf082625 completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c846043ed48190b6fa45ed0e70b4d3 completed March 28, 2026, 9:20 p.m.
Created at: March 27, 2026, 3:43 p.m.