Triple

T17956518
Position Surface form Disambiguated ID Type / Status
Subject Zhaoqing E448964 entity
Predicate hasSubdivision P747 FINISHED
Object Dinghu District
Dinghu District is an administrative urban district of Zhaoqing City in Guangdong Province, China, known for its scenic landscapes and ecological reserves.
E1416098 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: Dinghu District | Statement: [Zhaoqing, hasSubdivision, Dinghu District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinghu District
Context triple: [Zhaoqing, hasSubdivision, Dinghu District]
  • A. Shunqing District
    Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
  • B. Yuhua District
    Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • C. Lianshan District
    Lianshan District is an urban administrative district of Huludao City in Liaoning Province, northeastern China.
  • D. Dongchangfu District
    Dongchangfu District is the central urban district and administrative seat of Liaocheng in Shandong Province, China.
  • 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: Dinghu District
Triple: [Zhaoqing, hasSubdivision, Dinghu District]
Generated description
Dinghu District is an administrative urban district of Zhaoqing City in Guangdong Province, China, known for its scenic landscapes and ecological reserves.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dinghu District
Target entity description: Dinghu District is an administrative urban district of Zhaoqing City in Guangdong Province, China, known for its scenic landscapes and ecological reserves.
  • A. Shunqing District
    Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
  • B. Yuhua District
    Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • C. Lianshan District
    Lianshan District is an urban administrative district of Huludao City in Liaoning Province, northeastern China.
  • D. Dongchangfu District
    Dongchangfu District is the central urban district and administrative seat of Liaocheng in Shandong Province, China.
  • 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4afb0afe08190964e771ec632fa1e completed April 19, 2026, 10:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a083c5cfcb8819093bba494d48775ff completed May 16, 2026, 9:43 a.m.
NEDg Description generation batch_6a083da579ac8190abd33275c217b1e2 completed May 16, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_6a083e49d5988190b41e8ce5bcebeca5 completed May 16, 2026, 9:52 a.m.
Created at: April 10, 2026, 10:21 a.m.