Triple

T23500817
Position Surface form Disambiguated ID Type / Status
Subject A104 highway E571836 entity
Predicate connectsCity P4245 FINISHED
Object Nakuru E85650 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: Nakuru | Statement: [A104 highway, connectsCity, Nakuru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nakuru
Context triple: [A104 highway, connectsCity, Nakuru]
  • A. Nakuru chosen
    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.
  • B. Nakur
    Nakur is a small town in the Saharanpur district of Uttar Pradesh, India, known for its local markets and role as a regional administrative and commercial center.
  • C. Kajiado
    Kajiado is a town in southern Kenya that serves as an administrative and commercial center for the surrounding Maasai-inhabited region.
  • D. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • E. Nyamira
    Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
  • 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_69e245b4829881909b77a70e942bbd54 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a8fc37908190af86a01ab85737d6 completed April 29, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c8275e2bc8190a908d41a9824f2f8 completed May 19, 2026, 3:32 p.m.
Created at: April 17, 2026, 6:06 p.m.