Triple

T14634111
Position Surface form Disambiguated ID Type / Status
Subject Liulichang E343555 entity
Predicate hasSection P35 FINISHED
Object East Liulichang
East Liulichang is the eastern portion of Beijing’s historic Liulichang cultural street, known for its traditional shops selling antiques, calligraphy, paintings, and scholarly supplies.
 E1110682 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: East Liulichang | Statement: [Liulichang, hasSection, East Liulichang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: East Liulichang
Context triple: [Liulichang, hasSection, East Liulichang]
  • A. Lüshun
    Lüshun is a strategically important port city in northeastern China, historically known as Port Arthur and noted for its role in several major conflicts.
  • B. Longchang
    Longchang was a Chinese era name used during the Northern Qi dynasty to designate a specific reign period.
  • C. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • D. Xiping
    Xiping was an era name used during the reign of Emperor Ling in the late Eastern Han dynasty of China.
  • E. Lingbo
    Lingbo is a small village in central Sweden located within Ockelbo Municipality in Gävleborg County.
  • 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: East Liulichang
Triple: [Liulichang, hasSection, East Liulichang]
Generated description
East Liulichang is the eastern portion of Beijing’s historic Liulichang cultural street, known for its traditional shops selling antiques, calligraphy, paintings, and scholarly supplies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: East Liulichang
Target entity description: East Liulichang is the eastern portion of Beijing’s historic Liulichang cultural street, known for its traditional shops selling antiques, calligraphy, paintings, and scholarly supplies.
  • A. Lüshun
    Lüshun is a strategically important port city in northeastern China, historically known as Port Arthur and noted for its role in several major conflicts.
  • B. Longchang
    Longchang was a Chinese era name used during the Northern Qi dynasty to designate a specific reign period.
  • C. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • D. Xiping
    Xiping was an era name used during the reign of Emperor Ling in the late Eastern Han dynasty of China.
  • E. Lingbo
    Lingbo is a small village in central Sweden located within Ockelbo Municipality in Gävleborg County.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4aa7cb48190b008bd6b0e162c89 completed April 14, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda933937881909f3cf59fba878dfd completed May 8, 2026, 9:13 a.m.
NEDg Description generation batch_69fdb3efb4fc8190bca7469d89a66a85 completed May 8, 2026, 9:59 a.m.
NED2 Entity disambiguation (via description) batch_69fdb48b5ca08190be61da2fdb7dbce4 completed May 8, 2026, 10:01 a.m.
Created at: April 10, 2026, 1:26 a.m.