Triple

T13320937
Position Surface form Disambiguated ID Type / Status
Subject Jinan Yaoqiang International Airport E317311 entity
Predicate namedAfter P63 FINISHED
Object Yaoqiang
Yaoqiang is the locality in Jinan, Shandong Province, China, whose name is used for Jinan Yaoqiang International Airport.
E1032921 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: Yaoqiang | Statement: [Jinan Yaoqiang International Airport, namedAfter, Yaoqiang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yaoqiang
Context triple: [Jinan Yaoqiang International Airport, namedAfter, Yaoqiang]
  • A. Qiang Ji
    Qiang Ji is a paleontologist known for his work on early mammalian fossils, including the description of the Cretaceous mammal Eomaia.
  • B. Xiong Yi
    Xiong Yi was the legendary early ruler credited with establishing the ancient Chinese state of Chu during the Zhou dynasty.
  • C. Yingchao
    Yingchao is the given name of Deng Yingchao, a prominent Chinese revolutionary leader and influential politician in the 20th century.
  • D. Younan Xia
    Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
  • E. Zhang Mo
    Zhang Mo is a Chinese actor and film director, best known as the son of acclaimed filmmaker Zhang Yimou and for his roles in Chinese television dramas and films.
  • 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: Yaoqiang
Triple: [Jinan Yaoqiang International Airport, namedAfter, Yaoqiang]
Generated description
Yaoqiang is the locality in Jinan, Shandong Province, China, whose name is used for Jinan Yaoqiang International Airport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Yaoqiang
Target entity description: Yaoqiang is the locality in Jinan, Shandong Province, China, whose name is used for Jinan Yaoqiang International Airport.
  • A. Qiang Ji
    Qiang Ji is a paleontologist known for his work on early mammalian fossils, including the description of the Cretaceous mammal Eomaia.
  • B. Xiong Yi
    Xiong Yi was the legendary early ruler credited with establishing the ancient Chinese state of Chu during the Zhou dynasty.
  • C. Yingchao
    Yingchao is the given name of Deng Yingchao, a prominent Chinese revolutionary leader and influential politician in the 20th century.
  • D. Younan Xia
    Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
  • E. Zhang Mo
    Zhang Mo is a Chinese actor and film director, best known as the son of acclaimed filmmaker Zhang Yimou and for his roles in Chinese television dramas and films.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9992ab83c8190982d9f54dff6919f completed April 11, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716ee695c81909ffeeb0901ee66c1 completed May 3, 2026, 9:35 a.m.
NEDg Description generation batch_69f717f4d80c8190a1a95c0f2c83c563 completed May 3, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_69f718b994188190b273cc6116919c22 completed May 3, 2026, 9:43 a.m.
Created at: April 9, 2026, 9:30 p.m.