Triple

T648478
Position Surface form Disambiguated ID Type / Status
Subject Kenya E11292 entity
Predicate majorCity P316 FINISHED
Object 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.
 E85650 NE FINISHED

How this triple was built (4 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: [Kenya, majorCity, Nakuru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nakuru
Context triple: [Kenya, majorCity, Nakuru]
  • A. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • B. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • C. Mawenzi
    Mawenzi is the jagged, eroded eastern peak of Mount Kilimanjaro and one of its three main volcanic cones.
  • D. Kigoma
    Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
  • E. Moshi
    Moshi is a Tanzanian town in the Kilimanjaro Region that serves as a major gateway and base for climbers ascending Mount Kilimanjaro.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nakuru
Triple: [Kenya, majorCity, Nakuru]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nakuru
Target entity description: 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.
  • A. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • B. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • C. Mawenzi
    Mawenzi is the jagged, eroded eastern peak of Mount Kilimanjaro and one of its three main volcanic cones.
  • D. Kigoma
    Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
  • E. Moshi
    Moshi is a Tanzanian town in the Kilimanjaro Region that serves as a major gateway and base for climbers ascending Mount Kilimanjaro.
  • F. None of above. chosen

Provenance (5 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f308f34819094ba28cfc786051e completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc93fd28819088ece7790ff19270 completed March 2, 2026, 6:53 p.m.
NEDg Description generation batch_69a5debae16081909f167598cb20dbf6 completed March 2, 2026, 7:02 p.m.
NED2 Entity disambiguation (via description) batch_69a5fe46b8f48190b6a7e96fcac30d9f completed March 2, 2026, 9:16 p.m.
Created at: March 1, 2026, 7:36 p.m.