Triple

T9793756
Position Surface form Disambiguated ID Type / Status
Subject Nyanza region E237667 entity
Predicate hasTown P847 FINISHED
Object Nyamira
Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
 E830437 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: Nyamira | Statement: [Nyanza region, hasTown, Nyamira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nyamira
Context triple: [Nyanza region, hasTown, Nyamira]
  • A. Nanyuki
    Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
  • B. Nyazura
    Nyazura is a small town in eastern Zimbabwe situated along the main road and railway linking Harare and Mutare.
  • 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. 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.
  • 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. 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: Nyamira
Triple: [Nyanza region, hasTown, Nyamira]
Generated description
Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nyamira
Target entity description: Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
  • A. Nanyuki
    Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
  • B. Nyazura
    Nyazura is a small town in eastern Zimbabwe situated along the main road and railway linking Harare and Mutare.
  • 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. 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.
  • 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. 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_69ca84dc04488190b9c91193976c0960 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda347b6bc8190a99b7dec1650cd46 completed April 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d22866aea48190933524839241869a completed April 5, 2026, 9:16 a.m.
NEDg Description generation batch_69d22990ef5881908b6a6100d7dcf6e6 completed April 5, 2026, 9:21 a.m.
NED2 Entity disambiguation (via description) batch_69d22a0cb0808190a6119dc0268c50b9 completed April 5, 2026, 9:23 a.m.
Created at: March 30, 2026, 8:28 p.m.