Triple

T21519948
Position Surface form Disambiguated ID Type / Status
Subject 都筑郡 E530945 entity
Predicate 関連区 P61858 FINISHED
Object 港北区
港北区は、横浜市北部に位置し、住宅地と商業施設が混在するベッドタウン的性格を持つ行政区です。
 E1488673 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: 港北区 | Statement: [都筑郡, 関連区, 港北区]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 港北区
Context triple: [都筑郡, 関連区, 港北区]
  • A. Qinzhou District
    Qinzhou District is an urban district of Tianshui in Gansu Province, China, serving as one of the city’s central administrative and commercial areas.
  • B. Pingshan District
    Pingshan District is an administrative district in the eastern part of Shenzhen, China, known for its emerging high-tech industries and rapid urban development.
  • C. Pingshan District
    Pingshan District is an urban administrative district under the jurisdiction of Benxi City in Liaoning Province, China, known for its role in the region’s industrial and residential development.
  • D. Beihai Haicheng District
    Beihai Haicheng District is a central urban district of Beihai City in Guangxi, China, known as an administrative and commercial hub along the Gulf of Tonkin.
  • E. Xinbei District
    Xinbei District is a major urban district and economic hub of Changzhou in Jiangsu Province, China, known for its modern development and industrial zones.
  • 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: 港北区
Triple: [都筑郡, 関連区, 港北区]
Generated description
港北区は、横浜市北部に位置し、住宅地と商業施設が混在するベッドタウン的性格を持つ行政区です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 港北区
Target entity description: 港北区は、横浜市北部に位置し、住宅地と商業施設が混在するベッドタウン的性格を持つ行政区です。
  • A. Qinzhou District
    Qinzhou District is an urban district of Tianshui in Gansu Province, China, serving as one of the city’s central administrative and commercial areas.
  • B. Pingshan District
    Pingshan District is an administrative district in the eastern part of Shenzhen, China, known for its emerging high-tech industries and rapid urban development.
  • C. Pingshan District
    Pingshan District is an urban administrative district under the jurisdiction of Benxi City in Liaoning Province, China, known for its role in the region’s industrial and residential development.
  • D. Beihai Haicheng District
    Beihai Haicheng District is a central urban district of Beihai City in Guangxi, China, known as an administrative and commercial hub along the Gulf of Tonkin.
  • E. Xinbei District
    Xinbei District is a major urban district and economic hub of Changzhou in Jiangsu Province, China, known for its modern development and industrial zones.
  • 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_69e0c45d95a081908e7962ad215da746 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee884af0f08190bc1f3d70e57a325d completed April 26, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a09e82521248190b6b84a3074d70be1 completed May 17, 2026, 4:09 p.m.
NEDg Description generation batch_6a09e92969c881908b865da9d78cc48e completed May 17, 2026, 4:13 p.m.
NED2 Entity disambiguation (via description) batch_6a09e9ad9da08190b222b06c41734994 completed May 17, 2026, 4:15 p.m.
Created at: April 16, 2026, 6:26 p.m.