Triple

T3015374
Position Surface form Disambiguated ID Type / Status
Subject Fengtai District E82323 entity
Predicate contains P35 FINISHED
Object Nanyuan
Nanyuan is a locality in Beijing, China, situated within the city's Fengtai District.
 E317835 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: Nanyuan | Statement: [Fengtai District, contains, Nanyuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nanyuan
Context triple: [Fengtai District, contains, Nanyuan]
  • A. Gongqingtuan
    Gongqingtuan is the youth wing of the Chinese Communist Party, responsible for engaging and organizing young people in political education and social activities in China.
  • B. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • C. Kangqiao
    Kangqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities, international schools, and growing commercial development.
  • D. Xinzhuang
    Xinzhuang is a major suburban town and transportation hub in Shanghai, China, known for its busy commercial areas and key metro and rail connections.
  • E. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • 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: Nanyuan
Triple: [Fengtai District, contains, Nanyuan]
Generated description
Nanyuan is a locality in Beijing, China, situated within the city's Fengtai District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nanyuan
Target entity description: Nanyuan is a locality in Beijing, China, situated within the city's Fengtai District.
  • A. Gongqingtuan
    Gongqingtuan is the youth wing of the Chinese Communist Party, responsible for engaging and organizing young people in political education and social activities in China.
  • B. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • C. Kangqiao
    Kangqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities, international schools, and growing commercial development.
  • D. Xinzhuang
    Xinzhuang is a major suburban town and transportation hub in Shanghai, China, known for its busy commercial areas and key metro and rail connections.
  • E. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a6b37288190a6965d183ca4b08b completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e6b78448190beb41460314278ec completed March 11, 2026, 8:57 a.m.
NEDg Description generation batch_69b12faf75ac81909031430d58919c95 completed March 11, 2026, 9:02 a.m.
NED2 Entity disambiguation (via description) batch_69b1c7d3f2c88190aa26d8d12777b2a2 completed March 11, 2026, 7:51 p.m.
Created at: March 8, 2026, 3 p.m.