Triple

T5075658
Position Surface form Disambiguated ID Type / Status
Subject Heilongjiang E114388 entity
Predicate containsCity P294 FINISHED
Object Suihua
Suihua is a prefecture-level city in northeastern China known for its agricultural production and cold climate.
 E493946 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: Suihua | Statement: [Heilongjiang, containsCity, Suihua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Suihua
Context triple: [Heilongjiang, containsCity, Suihua]
  • A. Wuyuan
    Wuyuan is a historic county in northeastern Jiangxi, China, famed for its well-preserved Huizhou-style architecture and picturesque rural landscapes.
  • B. Heqing
    Heqing was an era name used during the Northern Qi dynasty in imperial China to designate a specific reign period.
  • C. Yuxiang
    Yuxiang is a Chinese given name notably borne by the early 20th-century warlord and military leader Feng Yuxiang.
  • D. Juxian
    Juxian is a county-level city in eastern China's Shandong province, known for its agricultural production and location on the Shandong Peninsula.
  • E. Luohe
    Luohe is a prefecture-level city in central Henan Province, China, known as an important regional transport and industrial hub.
  • 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: Suihua
Triple: [Heilongjiang, containsCity, Suihua]
Generated description
Suihua is a prefecture-level city in northeastern China known for its agricultural production and cold climate.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Suihua
Target entity description: Suihua is a prefecture-level city in northeastern China known for its agricultural production and cold climate.
  • A. Wuyuan
    Wuyuan is a historic county in northeastern Jiangxi, China, famed for its well-preserved Huizhou-style architecture and picturesque rural landscapes.
  • B. Heqing
    Heqing was an era name used during the Northern Qi dynasty in imperial China to designate a specific reign period.
  • C. Yuxiang
    Yuxiang is a Chinese given name notably borne by the early 20th-century warlord and military leader Feng Yuxiang.
  • D. Juxian
    Juxian is a county-level city in eastern China's Shandong province, known for its agricultural production and location on the Shandong Peninsula.
  • E. Luohe
    Luohe is a prefecture-level city in central Henan Province, China, known as an important regional transport and industrial hub.
  • 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_69bd443dbf908190a9401e9c2dc7bd7d completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74d2243481908c1ae62f7123c4e9 completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba6be1248190bad40b869c8d0820 completed March 21, 2026, 3:34 p.m.
NEDg Description generation batch_69bebb7ec9848190a9a9319b09dd9de3 completed March 21, 2026, 3:38 p.m.
NED2 Entity disambiguation (via description) batch_69bebc1642fc8190ae1acb68f01093c2 completed March 21, 2026, 3:41 p.m.
Created at: March 20, 2026, 1:39 p.m.