Triple

T15265727
Position Surface form Disambiguated ID Type / Status
Subject Quzhou E364895 entity
Predicate hasDistrict P459 FINISHED
Object Kecheng District
Kecheng District is the central urban district and administrative seat of Quzhou City in Zhejiang Province, China.
E1226731 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: Kecheng District | Statement: [Quzhou, hasDistrict, Kecheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kecheng District
Context triple: [Quzhou, hasDistrict, Kecheng District]
  • A. Tianxin District
    Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
  • B. Longquanyi District
    Longquanyi District is an urban district of Chengdu in Sichuan Province, China, known for its rapid development and sports facilities.
  • C. Xiqing District
    Xiqing District is an administrative district in the southwestern part of Tianjin, China, known for its mix of urban development, transportation hubs, and industrial zones.
  • D. Yuanbao District
    Yuanbao District is an urban administrative district within the city of Dandong in Liaoning Province, northeastern China.
  • E. Hongqi District
    Hongqi District is an urban administrative district within the prefecture-level city of Xinxiang in Henan Province, China.
  • 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: Kecheng District
Triple: [Quzhou, hasDistrict, Kecheng District]
Generated description
Kecheng District is the central urban district and administrative seat of Quzhou City in Zhejiang Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kecheng District
Target entity description: Kecheng District is the central urban district and administrative seat of Quzhou City in Zhejiang Province, China.
  • A. Tianxin District
    Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
  • B. Longquanyi District
    Longquanyi District is an urban district of Chengdu in Sichuan Province, China, known for its rapid development and sports facilities.
  • C. Xiqing District
    Xiqing District is an administrative district in the southwestern part of Tianjin, China, known for its mix of urban development, transportation hubs, and industrial zones.
  • D. Yuanbao District
    Yuanbao District is an urban administrative district within the city of Dandong in Liaoning Province, northeastern China.
  • E. Hongqi District
    Hongqi District is an urban administrative district within the prefecture-level city of Xinxiang in Henan Province, China.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00851c5b88190a296b6a105d3ee30 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a1d8e088190a2168952ab5dc687 completed May 10, 2026, 1:37 p.m.
NEDg Description generation batch_6a008b1b3bcc81908b1b811ed42205ec completed May 10, 2026, 1:41 p.m.
NED2 Entity disambiguation (via description) batch_6a008b7c29e88190b5a049cb2e541a8f completed May 10, 2026, 1:43 p.m.
Created at: April 10, 2026, 3:14 a.m.