Triple

T15474587
Position Surface form Disambiguated ID Type / Status
Subject Hebi E376751 entity
Predicate hasSubdivision P747 FINISHED
Object Shancheng District
Shancheng District is an urban administrative district of the prefecture-level city of Hebi in Henan Province, China.
E1250359 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: Shancheng District | Statement: [Hebi, hasSubdivision, Shancheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shancheng District
Context triple: [Hebi, hasSubdivision, Shancheng District]
  • A. Shuocheng District
    Shuocheng District is the central urban district and administrative heart of Shuozhou City in Shanxi Province, China.
  • B. Shunqing District
    Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
  • C. Chengguan District
    Chengguan District is the central urban district and administrative, commercial, and cultural core of Lanzhou, the capital of Gansu Province in northwestern China.
  • D. Chengguan District
    Chengguan District is the central urban district of Lhasa, serving as the political, economic, and cultural core of the Tibet Autonomous Region's capital city.
  • E. Jianhua District
    Jianhua District is a central urban district of Qiqihar City in Heilongjiang Province, northeastern China.
  • 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: Shancheng District
Triple: [Hebi, hasSubdivision, Shancheng District]
Generated description
Shancheng District is an urban administrative district of the prefecture-level city of Hebi in Henan Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Shancheng District
Target entity description: Shancheng District is an urban administrative district of the prefecture-level city of Hebi in Henan Province, China.
  • A. Shuocheng District
    Shuocheng District is the central urban district and administrative heart of Shuozhou City in Shanxi Province, China.
  • B. Shunqing District
    Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
  • C. Chengguan District
    Chengguan District is the central urban district and administrative, commercial, and cultural core of Lanzhou, the capital of Gansu Province in northwestern China.
  • D. Chengguan District
    Chengguan District is the central urban district of Lhasa, serving as the political, economic, and cultural core of the Tibet Autonomous Region's capital city.
  • E. Jianhua District
    Jianhua District is a central urban district of Qiqihar City in Heilongjiang Province, northeastern China.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6e859481909c3d08343b7ad27c completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0139e10e94819092b71606dbe4f5d5 completed May 11, 2026, 2:07 a.m.
NEDg Description generation batch_6a013ae388548190b09d2c81e1ab0d02 completed May 11, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_6a013b4df74c81908b3b99e276531e13 completed May 11, 2026, 2:13 a.m.
Created at: April 10, 2026, 3:34 a.m.