Triple

T7019349
Position Surface form Disambiguated ID Type / Status
Subject Jambojet E162778 entity
Predicate cityServed P82 FINISHED
Object Kisumu E43852 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: Kisumu | Statement: [Jambojet, cityServed, Kisumu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kisumu
Context triple: [Jambojet, cityServed, Kisumu]
  • A. Kisumu chosen
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • B. 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.
  • C. Eldoret
    Eldoret is a major town in western Kenya known as an agricultural and commercial hub and as a center for world-class long-distance runners.
  • D. Embakasi
    Embakasi is a residential and industrial area in Nairobi, Kenya, known for hosting key infrastructure and serving as a major gateway corridor to the city.
  • E. Nyanga
    Nyanga is a township on the Cape Flats near Cape Town, South Africa, known for its history of apartheid-era resistance and ongoing social and economic challenges.
  • 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_69c6885b26248190a857541e3d10e299 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1e8e36c81908c95a8181781cda4 completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c775707e30819088b311a1a87eee79 completed March 28, 2026, 6:30 a.m.
Created at: March 27, 2026, 2:34 p.m.