Triple

T5690489
Position Surface form Disambiguated ID Type / Status
Subject Taishanese E125416 entity
Predicate spokenIn P2266 FINISHED
Object Enping
Enping is a county-level city in Guangdong Province, China, known as part of the Sze Yup region and for its significant overseas Chinese diaspora.
 E541866 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: Enping | Statement: [Taishanese, spokenIn, Enping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Enping
Context triple: [Taishanese, spokenIn, Enping]
  • A. Wanning
    Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
  • B. Haozhou
    Haozhou is a historical city in China, known as the birthplace of the Hongwu Emperor, founder of the Ming dynasty.
  • C. Haining
    Haining is a county-level city in Zhejiang Province, China, known for its dramatic tidal bore on the Qiantang River and its textile industry.
  • D. Haikou
    Haikou is the capital and largest city of China’s Hainan Province, known as a key port, commercial hub, and tropical coastal destination.
  • E. Hui’an
    Hui’an is the art name (courtesy name) of Zhu Xi, the influential 12th-century Neo-Confucian philosopher and scholar of the Southern Song dynasty.
  • 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: Enping
Triple: [Taishanese, spokenIn, Enping]
Generated description
Enping is a county-level city in Guangdong Province, China, known as part of the Sze Yup region and for its significant overseas Chinese diaspora.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Enping
Target entity description: Enping is a county-level city in Guangdong Province, China, known as part of the Sze Yup region and for its significant overseas Chinese diaspora.
  • A. Wanning
    Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
  • B. Haozhou
    Haozhou is a historical city in China, known as the birthplace of the Hongwu Emperor, founder of the Ming dynasty.
  • C. Haining
    Haining is a county-level city in Zhejiang Province, China, known for its dramatic tidal bore on the Qiantang River and its textile industry.
  • D. Haikou
    Haikou is the capital and largest city of China’s Hainan Province, known as a key port, commercial hub, and tropical coastal destination.
  • E. Hui’an
    Hui’an is the art name (courtesy name) of Zhu Xi, the influential 12th-century Neo-Confucian philosopher and scholar of the Southern Song dynasty.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e340a08190b6175fad3e9a32b6 completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a47457c8190bc75f11a7f011a8a completed March 22, 2026, 9:08 p.m.
NEDg Description generation batch_69c05dc222e88190a1d715392ae24f08 completed March 22, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_69c0620ee1848190935f5f78abbed7ba completed March 22, 2026, 9:41 p.m.
Created at: March 22, 2026, 3:44 p.m.