Triple

T4217264
Position Surface form Disambiguated ID Type / Status
Subject Juyongguan E94248 entity
Predicate near P350 FINISHED
Object Nankou
Nankou is a town in Beijing’s Changping District known as a key gateway area near the Juyongguan section of the Great Wall.
 E425219 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: Nankou | Statement: [Juyongguan, near, Nankou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nankou
Context triple: [Juyongguan, near, Nankou]
  • A. Caishikou
    Caishikou is a subway station in central Beijing that serves as an important stop on the city’s urban rail network.
  • B. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • C. Jinqiao
    Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
  • D. Hanyang
    Hanyang is a historic district and former city now incorporated into Wuhan in Hubei Province, China, known for its early industrial development and strategic location at the confluence of the Han and Yangtze rivers.
  • E. Yangsan
    Yangsan is a city in South Gyeongsang Province, South Korea, known as a growing residential and educational hub near Busan.
  • 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: Nankou
Triple: [Juyongguan, near, Nankou]
Generated description
Nankou is a town in Beijing’s Changping District known as a key gateway area near the Juyongguan section of the Great Wall.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nankou
Target entity description: Nankou is a town in Beijing’s Changping District known as a key gateway area near the Juyongguan section of the Great Wall.
  • A. Caishikou
    Caishikou is a subway station in central Beijing that serves as an important stop on the city’s urban rail network.
  • B. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • C. Jinqiao
    Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
  • D. Hanyang
    Hanyang is a historic district and former city now incorporated into Wuhan in Hubei Province, China, known for its early industrial development and strategic location at the confluence of the Han and Yangtze rivers.
  • E. Yangsan
    Yangsan is a city in South Gyeongsang Province, South Korea, known as a growing residential and educational hub near Busan.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34beb470481909ceff19195417f19 completed March 12, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a855cfc08190acceced9cb80f41a completed March 14, 2026, 6:26 p.m.
NEDg Description generation batch_69b5a8e024a081909e7ecbe969793281 completed March 14, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_69b5acefd1f881908226ff68a741552b completed March 14, 2026, 6:46 p.m.
Created at: March 12, 2026, 11:04 p.m.