Triple

T4008096
Position Surface form Disambiguated ID Type / Status
Subject Haidian District E89575 entity
Predicate contains P35 FINISHED
Object Qinghe
Qinghe is a subdistrict in Beijing’s Haidian District, known primarily as a residential and administrative area within the city’s northwestern urban zone.
 E407786 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: Qinghe | Statement: [Haidian District, contains, Qinghe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Qinghe
Context triple: [Haidian District, contains, Qinghe]
  • A. Longqing
    Longqing was the era name of a brief but notable period of the Ming dynasty in China, associated with the reign of the Longqing Emperor in the 16th century.
  • B. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • C. Yuanhong
    Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
  • D. Qichao
    Qichao is the given name of Liang Qichao, a prominent late Qing and early Republican Chinese scholar, journalist, and reformist thinker.
  • E. 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.
  • 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: Qinghe
Triple: [Haidian District, contains, Qinghe]
Generated description
Qinghe is a subdistrict in Beijing’s Haidian District, known primarily as a residential and administrative area within the city’s northwestern urban zone.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Qinghe
Target entity description: Qinghe is a subdistrict in Beijing’s Haidian District, known primarily as a residential and administrative area within the city’s northwestern urban zone.
  • A. Longqing
    Longqing was the era name of a brief but notable period of the Ming dynasty in China, associated with the reign of the Longqing Emperor in the 16th century.
  • B. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • C. Yuanhong
    Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
  • D. Qichao
    Qichao is the given name of Liang Qichao, a prominent late Qing and early Republican Chinese scholar, journalist, and reformist thinker.
  • E. 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.
  • 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa647f80819081180eb267f1cfcc completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55626f19c8190af4705b1cd3b201d completed March 14, 2026, 12:35 p.m.
NEDg Description generation batch_69b556efc2148190a66e732e09e4fc21 completed March 14, 2026, 12:39 p.m.
NED2 Entity disambiguation (via description) batch_69b5575de0e88190843f1fcbc12c9dd5 completed March 14, 2026, 12:41 p.m.
Created at: March 9, 2026, 3:34 p.m.