Triple

T14998443
Position Surface form Disambiguated ID Type / Status
Subject Moshi Rural District E374019 entity
Predicate borders P224 FINISHED
Object Moshi Urban District E76525 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: Moshi Urban District | Statement: [Moshi Rural District, borders, Moshi Urban District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moshi Urban District
Context triple: [Moshi Rural District, borders, Moshi Urban District]
  • A. Moshi chosen
    Moshi is a Tanzanian town in the Kilimanjaro Region that serves as a major gateway and base for climbers ascending Mount Kilimanjaro.
  • B. Moshi District Council
    Moshi District Council is the local government authority responsible for administering and providing public services in Moshi Rural District in Tanzania.
  • C. Kilwa District
    Kilwa District is an administrative district in Tanzania’s Lindi Region that includes the historic Swahili coastal settlement and UNESCO World Heritage Site of Kilwa Kisiwani.
  • D. Tsavo town
    Tsavo town is a small settlement in southeastern Kenya that serves as a gateway to the nearby Tsavo East and Tsavo West National Parks.
  • E. Thika
    Thika is a major industrial and commercial town in central Kenya, known for its manufacturing sector and proximity to Nairobi.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded71a5618819083ae96a79735ef98 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dcbd7c88190ad1a302cd0c6ef28 completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 2:54 a.m.