Triple

T14998541
Position Surface form Disambiguated ID Type / Status
Subject Siha District E374021 entity
Predicate nearbyMajorCity P1982 FINISHED
Object Moshi 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 | Statement: [Siha District, nearbyMajorCity, Moshi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moshi
Context triple: [Siha District, nearbyMajorCity, Moshi]
  • 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. Juja
    Juja is a rapidly growing urban town in Kenya known for its proximity to Nairobi and its major universities and industries.
  • C. Limuru
    Limuru is a highland town in central Kenya known for its cool climate, tea plantations, and proximity to Nairobi.
  • D. 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.
  • 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_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_69feb7d956808190a3f17ef14c21d3af completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 2:54 a.m.