Triple

T15745847
Position Surface form Disambiguated ID Type / Status
Subject Rift Valley Province E381719 entity
Predicate containsLake P1025 FINISHED
Object Lake Bogoria E729234 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: Lake Bogoria | Statement: [Rift Valley Province, containsLake, Lake Bogoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Bogoria
Context triple: [Rift Valley Province, containsLake, Lake Bogoria]
  • A. Lake Bogoria chosen
    Lake Bogoria is a saline, alkaline lake in Kenya’s Rift Valley famous for its hot springs, geysers, and large flocks of flamingos.
  • B. Lake Nakuru
    Lake Nakuru is a shallow alkaline lake in Kenya’s Rift Valley, famed for its large populations of flamingos and diverse wildlife within Lake Nakuru National Park.
  • C. Lake Eyasi
    Lake Eyasi is a shallow, seasonal saline lake in northern Tanzania, known for its remote setting near the Serengeti and as home to the Hadza hunter-gatherer people.
  • D. Lake Manyara
    Lake Manyara is a shallow alkaline lake in northern Tanzania, renowned for its diverse birdlife, large flocks of flamingos, and the surrounding Lake Manyara National Park.
  • E. Lake Naivasha
    Lake Naivasha is a freshwater lake in Kenya’s Great Rift Valley, renowned for its rich birdlife, hippo populations, and surrounding flower farms and wildlife conservancies.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0502c0c3c8190b8e512df307039c1 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa129a6448190affdee9d0b1362bc completed May 9, 2026, 9:03 p.m.
Created at: April 10, 2026, 4:46 a.m.