Triple

T9034915
Position Surface form Disambiguated ID Type / Status
Subject Nairobi Metropolitan Region E216466 entity
Predicate containsTown P847 FINISHED
Object Juja E768597 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: Juja | Statement: [Nairobi Metropolitan Region, containsTown, Juja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juja
Context triple: [Nairobi Metropolitan Region, containsTown, Juja]
  • A. Juja chosen
    Juja is a rapidly growing urban town in Kenya known for its proximity to Nairobi and its major universities and industries.
  • B. Moshi
    Moshi is a Tanzanian town in the Kilimanjaro Region that serves as a major gateway and base for climbers ascending Mount Kilimanjaro.
  • C. Malindi
    Malindi is a historic coastal town in southeastern Kenya known for its beaches, Swahili culture, and role as a former trading port on the Indian Ocean.
  • 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. Nakuru
    Nakuru is a prominent Kenyan city in the Rift Valley region, known for its proximity to Lake Nakuru National Park and its role as an important agricultural and commercial center.
  • 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_69ca83d10b608190b2b2f8e0a7faaf14 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6abf4af481908d21245332329d99 completed April 1, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdbce352c8190b5862d0cc103bfdb completed April 3, 2026, 3:25 p.m.
Created at: March 30, 2026, 7:08 p.m.