Triple

T10956979
Position Surface form Disambiguated ID Type / Status
Subject Clock Tower (Arusha) E258870 entity
Predicate regionServed P82 FINISHED
Object Arusha urban area E45051 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: Arusha urban area | Statement: [Clock Tower (Arusha), regionServed, Arusha urban area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arusha urban area
Context triple: [Clock Tower (Arusha), regionServed, Arusha urban area]
  • A. Arusha Region
    Arusha Region is an administrative region in northern Tanzania known for its tourism hub city of Arusha and proximity to major national parks and Mount Kilimanjaro.
  • B. Arusha, Tanzania chosen
    Arusha, Tanzania is a major city in northern Tanzania known as a diplomatic hub and gateway to popular safari destinations and Mount Kilimanjaro.
  • C. Dodoma Region
    Dodoma Region is an administrative region in central Tanzania that includes the national capital city, Dodoma.
  • D. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • E. Oshakati
    Oshakati is a major northern Namibian town that serves as an important commercial and administrative hub.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d771260e9881909401a7a7466e1b8a completed April 9, 2026, 9:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4f34d1e108190ad281dae6c92634e completed April 19, 2026, 3:22 p.m.
Created at: April 8, 2026, 9:23 p.m.