Triple

T14998522
Position Surface form Disambiguated ID Type / Status
Subject Siha District E374021 entity
Predicate capital P234 FINISHED
Object Sanya Juu
Sanya Juu is a small town in northern Tanzania that serves as the administrative and commercial center of Siha District in the Kilimanjaro Region.
 E1131053 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: Sanya Juu | Statement: [Siha District, capital, Sanya Juu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sanya Juu
Context triple: [Siha District, capital, Sanya Juu]
  • A. Na San
    Na San is a locality in northwestern Vietnam known primarily as the site of a major French defensive victory over the Viet Minh during the First Indochina War.
  • B. Sanmu
    Sanmu is a coastal city in Chiba Prefecture, Japan, known for its proximity to the Pacific Ocean and popular seaside areas.
  • C. Hoan-ya
    Hoan-ya is an alternative name for the Hoanya language, an indigenous Formosan language historically spoken in Taiwan.
  • D. Fujinami
    Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
  • E. Tai Shani
    Tai Shani is a British contemporary artist known for her feminist, fantastical multimedia installations and as a joint winner of the 2019 Turner Prize.
  • 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: Sanya Juu
Triple: [Siha District, capital, Sanya Juu]
Generated description
Sanya Juu is a small town in northern Tanzania that serves as the administrative and commercial center of Siha District in the Kilimanjaro Region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sanya Juu
Target entity description: Sanya Juu is a small town in northern Tanzania that serves as the administrative and commercial center of Siha District in the Kilimanjaro Region.
  • A. Na San
    Na San is a locality in northwestern Vietnam known primarily as the site of a major French defensive victory over the Viet Minh during the First Indochina War.
  • B. Sanmu
    Sanmu is a coastal city in Chiba Prefecture, Japan, known for its proximity to the Pacific Ocean and popular seaside areas.
  • C. Hoan-ya
    Hoan-ya is an alternative name for the Hoanya language, an indigenous Formosan language historically spoken in Taiwan.
  • D. Fujinami
    Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
  • E. Tai Shani
    Tai Shani is a British contemporary artist known for her feminist, fantastical multimedia installations and as a joint winner of the 2019 Turner Prize.
  • 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.