Triple

T14998644
Position Surface form Disambiguated ID Type / Status
Subject Kajiado County E374024 entity
Predicate capital P234 FINISHED
Object Kajiado
Kajiado is a town in southern Kenya that serves as an administrative and commercial center for the surrounding Maasai-inhabited region.
 E1131067 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: Kajiado | Statement: [Kajiado County, capital, Kajiado]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kajiado
Context triple: [Kajiado County, capital, Kajiado]
  • A. 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.
  • B. Isiolo
    Isiolo is a town in central Kenya that serves as a key transport and commercial hub linking the country’s northern regions with the rest of the nation.
  • C. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • D. Wazaramo
    Wazaramo are a Bantu-speaking ethnic group native to the coastal and near-coastal regions around Dar es Salaam in eastern Tanzania.
  • E. Thika
    Thika is a major industrial and commercial town in central Kenya, known for its manufacturing sector and proximity to Nairobi.
  • 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: Kajiado
Triple: [Kajiado County, capital, Kajiado]
Generated description
Kajiado is a town in southern Kenya that serves as an administrative and commercial center for the surrounding Maasai-inhabited region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kajiado
Target entity description: Kajiado is a town in southern Kenya that serves as an administrative and commercial center for the surrounding Maasai-inhabited region.
  • A. 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.
  • B. Isiolo
    Isiolo is a town in central Kenya that serves as a key transport and commercial hub linking the country’s northern regions with the rest of the nation.
  • C. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • D. Wazaramo
    Wazaramo are a Bantu-speaking ethnic group native to the coastal and near-coastal regions around Dar es Salaam in eastern Tanzania.
  • E. Thika
    Thika is a major industrial and commercial town in central Kenya, known for its manufacturing sector and proximity to Nairobi.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded71a5618819083ae96a79735ef98 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969c3ba88190899f06b185e94ccf completed May 9, 2026, 2:06 a.m.
NEDg Description generation batch_69fe972728dc8190a9cf2a3e984b05a7 completed May 9, 2026, 2:08 a.m.
NED2 Entity disambiguation (via description) batch_69fe9790d1d081908fc94829d3104e07 completed May 9, 2026, 2:10 a.m.
Created at: April 10, 2026, 2:54 a.m.