Triple

T5884233
Position Surface form Disambiguated ID Type / Status
Subject Yue Chinese E130821 entity
Predicate hasVariety P455 FINISHED
Object Gao-Yang Yue
Gao-Yang Yue is a regional variety of Yue Chinese spoken primarily in parts of Guangdong province in southern China.
E554519 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: Gao-Yang Yue | Statement: [Yue Chinese, hasVariety, Gao-Yang Yue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gao-Yang Yue
Context triple: [Yue Chinese, hasVariety, Gao-Yang Yue]
  • A. Yanluo Wang
    Yanluo Wang is the Chinese deity who presides over the underworld and judges the souls of the dead.
  • B. Xue Yue
    Xue Yue was a prominent Nationalist Chinese general renowned for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
  • C. Yangqing Jia
    Yangqing Jia is a computer scientist and software engineer known for his influential work in deep learning and computer vision, including contributions to convolutional neural network architectures and open-source frameworks.
  • D. Zhu Junyi
    Zhu Junyi is a former senior Chinese police and security official best known for his involvement in major corruption scandals.
  • E. Gao Yang
    Gao Yang, better known as Emperor Wenxuan of Northern Qi, was the founding emperor of the Northern Qi dynasty in 6th-century 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: Gao-Yang Yue
Triple: [Yue Chinese, hasVariety, Gao-Yang Yue]
Generated description
Gao-Yang Yue is a regional variety of Yue Chinese spoken primarily in parts of Guangdong province in southern China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gao-Yang Yue
Target entity description: Gao-Yang Yue is a regional variety of Yue Chinese spoken primarily in parts of Guangdong province in southern China.
  • A. Yanluo Wang
    Yanluo Wang is the Chinese deity who presides over the underworld and judges the souls of the dead.
  • B. Xue Yue
    Xue Yue was a prominent Nationalist Chinese general renowned for his leadership in key battles against Japanese forces during the Second Sino-Japanese War.
  • C. Yangqing Jia
    Yangqing Jia is a computer scientist and software engineer known for his influential work in deep learning and computer vision, including contributions to convolutional neural network architectures and open-source frameworks.
  • D. Zhu Junyi
    Zhu Junyi is a former senior Chinese police and security official best known for his involvement in major corruption scandals.
  • E. Gao Yang
    Gao Yang, better known as Emperor Wenxuan of Northern Qi, was the founding emperor of the Northern Qi dynasty in 6th-century 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_69c0085628dc8190b334c1b44c067efc completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0367743508190bae211e9ce8f9690 completed March 22, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b13839f48190b23f22d5317eb571 completed March 23, 2026, 3:19 a.m.
NEDg Description generation batch_69c0b27438a08190ab6b72c8fd682bf6 completed March 23, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_69c0b309a70081908ad3e819879b17e4 completed March 23, 2026, 3:27 a.m.
Created at: March 22, 2026, 3:57 p.m.