Triple

T15585107
Position Surface form Disambiguated ID Type / Status
Subject Liaoyang E374598 entity
Predicate administers P123 FINISHED
Object Wensheng District NE ONDG

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: Wensheng District | Statement: [Liaoyang, administers, Wensheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wensheng District
Context triple: [Liaoyang, administers, Wensheng District]
  • A. 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.
  • B. Chengdong District
    Chengdong District is an urban administrative district of Xining, the capital city of Qinghai Province in northwestern China.
  • C. Tiefeng District
    Tiefeng District is an urban district of the city of Qiqihar in Heilongjiang Province, northeastern China.
  • D. Yunxi District
    Yunxi District is an urban administrative district of Yueyang City in Hunan Province, China, known for its location along the Yangtze River and Dongting Lake region.
  • E. Shizhong District
    Shizhong District is an urban administrative district that serves as the central area of Zaozhuang 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: Wensheng District
Triple: [Liaoyang, administers, Wensheng District]
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wensheng District
Target entity description: Wensheng District is an urban district within the prefecture-level city of Liaoyang in Liaoning Province, northeastern China.
  • A. 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.
  • B. Chengdong District
    Chengdong District is an urban administrative district of Xining, the capital city of Qinghai Province in northwestern China.
  • C. Tiefeng District
    Tiefeng District is an urban district of the city of Qiqihar in Heilongjiang Province, northeastern China.
  • D. Yunxi District
    Yunxi District is an urban administrative district of Yueyang City in Hunan Province, China, known for its location along the Yangtze River and Dongting Lake region.
  • E. Shizhong District
    Shizhong District is an urban administrative district that serves as the central area of Zaozhuang City in Shandong Province, China.
  • F. None of above. chosen

Provenance (4 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e47971481909e986dd999354628 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01953c493c819084850ab8e7f0d261 completed May 11, 2026, 8:37 a.m.
NEDg Description generation batch_6a01963971248190b5e2b0b77eb7cbfe in_progress May 11, 2026, 8:41 a.m.
Created at: April 10, 2026, 4:11 a.m.