Triple

T11736679
Position Surface form Disambiguated ID Type / Status
Subject Yibin E279044 entity
Predicate hasCitySeat P15001 FINISHED
Object Cuiping District
Cuiping District is the central urban district and administrative seat of Yibin City in Sichuan Province, China.
E954102 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: Cuiping District | Statement: [Yibin, hasCitySeat, Cuiping District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuiping District
Context triple: [Yibin, hasCitySeat, Cuiping District]
  • A. Zhifu District
    Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
  • B. Xiuying District
    Xiuying District is an urban administrative district of Haikou City on Hainan Island in southern China, known for its coastal location and role in the city's development.
  • C. Pingzhen District
    Pingzhen District is an urban district in northern Taiwan known as part of the rapidly developing Taoyuan metropolitan area.
  • D. Linwei District
    Linwei District is an urban administrative district in Weinan, Shaanxi Province, China, serving as the city's central political and economic area.
  • E. Kuiwen District
    Kuiwen District is an urban administrative district and commercial center of Weifang City in Shandong 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: Cuiping District
Triple: [Yibin, hasCitySeat, Cuiping District]
Generated description
Cuiping District is the central urban district and administrative seat of Yibin City in Sichuan Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cuiping District
Target entity description: Cuiping District is the central urban district and administrative seat of Yibin City in Sichuan Province, China.
  • A. Zhifu District
    Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
  • B. Xiuying District
    Xiuying District is an urban administrative district of Haikou City on Hainan Island in southern China, known for its coastal location and role in the city's development.
  • C. Pingzhen District
    Pingzhen District is an urban district in northern Taiwan known as part of the rapidly developing Taoyuan metropolitan area.
  • D. Linwei District
    Linwei District is an urban administrative district in Weinan, Shaanxi Province, China, serving as the city's central political and economic area.
  • E. Kuiwen District
    Kuiwen District is an urban administrative district and commercial center of Weifang City in Shandong 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4edced48190b7a59dd45921828e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43f739c2081909e8923290c139c6f completed May 1, 2026, 5:51 a.m.
NEDg Description generation batch_69f448f506a48190a0f1b89ad570fad5 completed May 1, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f44ad185cc8190893cf663cfed6980 completed May 1, 2026, 6:40 a.m.
Created at: April 8, 2026, 9:41 p.m.