Triple

T13021027
Position Surface form Disambiguated ID Type / Status
Subject Mutarazi Falls E326169 entity
Predicate nearSettlement P3883 FINISHED
Object Nyanga
Nyanga is a town and popular tourist destination in eastern Zimbabwe, known for its scenic highlands, national park, and proximity to major waterfalls and mountain landscapes.
 E1020680 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: Nyanga | Statement: [Mutarazi Falls, nearSettlement, Nyanga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nyanga
Context triple: [Mutarazi Falls, nearSettlement, Nyanga]
  • A. 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.
  • B. Nyamira
    Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
  • C. Nanyuki
    Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
  • D. Namanga
    Namanga is a small border town between Kenya and Tanzania that serves as a key gateway for tourists traveling to Amboseli National Park.
  • E. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • 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: Nyanga
Triple: [Mutarazi Falls, nearSettlement, Nyanga]
Generated description
Nyanga is a town and popular tourist destination in eastern Zimbabwe, known for its scenic highlands, national park, and proximity to major waterfalls and mountain landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nyanga
Target entity description: Nyanga is a town and popular tourist destination in eastern Zimbabwe, known for its scenic highlands, national park, and proximity to major waterfalls and mountain landscapes.
  • A. 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.
  • B. Nyamira
    Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
  • C. Nanyuki
    Nanyuki is a Kenyan town on the equator that serves as a popular gateway to Mount Kenya and the surrounding highland wilderness.
  • D. Namanga
    Namanga is a small border town between Kenya and Tanzania that serves as a key gateway for tourists traveling to Amboseli National Park.
  • E. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ecf21bc819082fb512bc479b4be completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5f861188190892b4d693395cc5e completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6d943a80c81909bc39b9a9ef303bd completed May 3, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69f6da1e56388190b536831b2c6d493f completed May 3, 2026, 5:16 a.m.
Created at: April 9, 2026, 8:52 p.m.