Triple

T15347514
Position Surface form Disambiguated ID Type / Status
Subject Benxi E366961 entity
Predicate hasSubdivision P747 FINISHED
Object Nanfen District
Nanfen District is an administrative district under the jurisdiction of the city of Benxi in Liaoning Province, northeastern China.
E1151803 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: Nanfen District | Statement: [Benxi, hasSubdivision, Nanfen District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanfen District
Context triple: [Benxi, hasSubdivision, Nanfen District]
  • A. Congtai District
    Congtai District is a central urban district of Handan City in Hebei Province, China, serving as one of its main administrative and commercial areas.
  • B. Yantan District
    Yantan District is an urban administrative district of Zigong, a prefecture-level city in Sichuan Province, China.
  • C. Wanbailin District
    Wanbailin District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
  • D. Zhen’an District
    Zhen’an District is an urban administrative district of the city of Dandong in Liaoning Province, northeastern China, located near the border with North Korea.
  • E. Shangzhou District
    Shangzhou District is an urban administrative district in Shangluo, Shaanxi Province, China, serving as the city's political and economic center.
  • 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: Nanfen District
Triple: [Benxi, hasSubdivision, Nanfen District]
Generated description
Nanfen District is an administrative district under the jurisdiction of the city of Benxi in Liaoning Province, northeastern China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nanfen District
Target entity description: Nanfen District is an administrative district under the jurisdiction of the city of Benxi in Liaoning Province, northeastern China.
  • A. Congtai District
    Congtai District is a central urban district of Handan City in Hebei Province, China, serving as one of its main administrative and commercial areas.
  • B. Yantan District
    Yantan District is an urban administrative district of Zigong, a prefecture-level city in Sichuan Province, China.
  • C. Wanbailin District
    Wanbailin District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
  • D. Zhen’an District
    Zhen’an District is an urban administrative district of the city of Dandong in Liaoning Province, northeastern China, located near the border with North Korea.
  • E. Shangzhou District
    Shangzhou District is an urban administrative district in Shangluo, Shaanxi Province, China, serving as the city's political and economic center.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e1749bc8190a8b9cbcb27288a5b completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01fb46b48190a030e40ee0163559 completed May 9, 2026, 9:44 a.m.
NEDg Description generation batch_69ff031869a481909911d251aa9ce3e8 completed May 9, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_69ff03c0ebc081908b1a132256e9d004 completed May 9, 2026, 9:52 a.m.
Created at: April 10, 2026, 3:17 a.m.