Triple

T2966391
Position Surface form Disambiguated ID Type / Status
Subject Kitami E80174 entity
Predicate hasSubdivision P747 FINISHED
Object Rubeshibe
Rubeshibe is a district within the city of Kitami in Hokkaido, Japan, known historically as a former town before its merger into the expanded municipality.
 E314761 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: Rubeshibe | Statement: [Kitami, hasSubdivision, Rubeshibe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rubeshibe
Context triple: [Kitami, hasSubdivision, Rubeshibe]
  • A. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • B. Oshiage
    Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
  • C. Baljurashi
    Baljurashi is a city in southwestern Saudi Arabia known for its mountainous terrain, cool climate, and location within the Al Bahah region.
  • D. Ushu
    Ushu is a scenic mountainous village in Pakistan’s Swat Valley, known for its lush forests, rivers, and access to trekking and natural viewpoints.
  • E. Shiso
    Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
  • 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: Rubeshibe
Triple: [Kitami, hasSubdivision, Rubeshibe]
Generated description
Rubeshibe is a district within the city of Kitami in Hokkaido, Japan, known historically as a former town before its merger into the expanded municipality.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rubeshibe
Target entity description: Rubeshibe is a district within the city of Kitami in Hokkaido, Japan, known historically as a former town before its merger into the expanded municipality.
  • A. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • B. Oshiage
    Oshiage is a district in Sumida, Tokyo, best known as the location of the Tokyo Skytree and its surrounding commercial complex.
  • C. Baljurashi
    Baljurashi is a city in southwestern Saudi Arabia known for its mountainous terrain, cool climate, and location within the Al Bahah region.
  • D. Ushu
    Ushu is a scenic mountainous village in Pakistan’s Swat Valley, known for its lush forests, rivers, and access to trekking and natural viewpoints.
  • E. Shiso
    Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
  • 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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad996e93788190ba9883714d4dfa0c completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc9fcfa48190a5e23ec1f3f01038 completed March 11, 2026, 5:24 a.m.
NEDg Description generation batch_69b100c1bfd48190ab71f460afb096e3 completed March 11, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69b10126bd788190b40f3ce1a8a547aa completed March 11, 2026, 5:44 a.m.
Created at: March 8, 2026, 2:58 p.m.