Triple

T16513584
Position Surface form Disambiguated ID Type / Status
Subject 六安 E401123 entity
Predicate hasSubdivision P747 FINISHED
Object 舒城县
舒城县 is a county under the administration of Lu’an City in Anhui Province, eastern China, known for its agricultural economy and location in the Dabie Mountain region.
 E1218408 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: 舒城县 | Statement: [六安, hasSubdivision, 舒城县]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 舒城县
Context triple: [六安, hasSubdivision, 舒城县]
  • A. 六安
    六安 is a prefecture-level city in western Anhui Province, China, known for its rich history and famous Lu'an Melon Seed tea.
  • B. Tongcheng County
    Tongcheng County is a county-level administrative region under the jurisdiction of Xianning City in southeastern Hubei Province, China, known for its rural landscapes and historical sites.
  • C. Gu'an County
    Gu'an County is an administrative county in northern China’s Hebei Province, situated just south of Beijing and forming part of the capital’s greater metropolitan area.
  • D. 黄州区
    黄州区 is an urban district under the jurisdiction of Huanggang City in Hubei Province, China, known as its political, economic, and cultural center.
  • E. 马鞍山
    马鞍山是位于中国安徽省东部、长江沿岸的一座以钢铁工业和山水景观著称的地级市。
  • 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: 舒城县
Triple: [六安, hasSubdivision, 舒城县]
Generated description
舒城县 is a county under the administration of Lu’an City in Anhui Province, eastern China, known for its agricultural economy and location in the Dabie Mountain region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 舒城县
Target entity description: 舒城县 is a county under the administration of Lu’an City in Anhui Province, eastern China, known for its agricultural economy and location in the Dabie Mountain region.
  • A. 六安
    六安 is a prefecture-level city in western Anhui Province, China, known for its rich history and famous Lu'an Melon Seed tea.
  • B. Tongcheng County
    Tongcheng County is a county-level administrative region under the jurisdiction of Xianning City in southeastern Hubei Province, China, known for its rural landscapes and historical sites.
  • C. Gu'an County
    Gu'an County is an administrative county in northern China’s Hebei Province, situated just south of Beijing and forming part of the capital’s greater metropolitan area.
  • D. 黄州区
    黄州区 is an urban district under the jurisdiction of Huanggang City in Hubei Province, China, known as its political, economic, and cultural center.
  • E. 马鞍山
    马鞍山是位于中国安徽省东部、长江沿岸的一座以钢铁工业和山水景观著称的地级市。
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e78d4848190a55de9902115b1b2 completed April 18, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0060827d988190b2c0c075a49dfde8 completed May 10, 2026, 10:40 a.m.
NEDg Description generation batch_6a006133a9148190af5bc0cec8ad6695 completed May 10, 2026, 10:42 a.m.
NED2 Entity disambiguation (via description) batch_6a0061c85d5481909628c2fddbcf0d54 completed May 10, 2026, 10:45 a.m.
Created at: April 10, 2026, 5:14 a.m.