Triple

T10109920
Position Surface form Disambiguated ID Type / Status
Subject hsn E218212 entity
Predicate hasDialect P4251 FINISHED
Object Qidong Xiang
Qidong Xiang is a variety of the Xiang group of Chinese dialects spoken primarily in Qidong County in Hunan Province, China.
 E656842 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: Qidong Xiang | Statement: [hsn, hasDialect, Qidong Xiang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Qidong Xiang
Context triple: [hsn, hasDialect, Qidong Xiang]
  • A. Qidong County
    Qidong County is an administrative county in Hunan Province, China, governed by the prefecture-level city of Hengyang.
  • B. Huixian
    Huixian is a county-level city administered by Xinxiang in Henan Province, China, known for its mix of urban development and surrounding rural landscapes.
  • C. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • D. Liyang
    Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
  • E. Dongqing
    Dongqing is a coastal village on Orchid Island in Taiwan, known for its indigenous Tao culture and scenic Pacific shoreline.
  • 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: Qidong Xiang
Triple: [hsn, hasDialect, Qidong Xiang]
Generated description
Qidong Xiang is a variety of the Xiang group of Chinese dialects spoken primarily in Qidong County in Hunan Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Qidong Xiang
Target entity description: Qidong Xiang is a variety of the Xiang group of Chinese dialects spoken primarily in Qidong County in Hunan Province, China.
  • A. Qidong County chosen
    Qidong County is an administrative county in Hunan Province, China, governed by the prefecture-level city of Hengyang.
  • B. Huixian
    Huixian is a county-level city administered by Xinxiang in Henan Province, China, known for its mix of urban development and surrounding rural landscapes.
  • C. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • D. Liyang
    Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
  • E. Dongqing
    Dongqing is a coastal village on Orchid Island in Taiwan, known for its indigenous Tao culture and scenic Pacific shoreline.
  • F. None of above.

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_69ca83da93fc8190b54e44bc2b34857c completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd0cdb3c88190a74f75bf865664f3 completed April 2, 2026, 2:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc1805d08190bc39aadf1e84a569 completed April 5, 2026, 8:54 p.m.
NEDg Description generation batch_69d2cd8f0a688190a437b7e2d158c70c completed April 5, 2026, 9:01 p.m.
NED2 Entity disambiguation (via description) batch_69d2ce422e4c8190b54b94cdfa0c4c98 completed April 5, 2026, 9:04 p.m.
Created at: March 30, 2026, 9:03 p.m.