Triple

T9483941
Position Surface form Disambiguated ID Type / Status
Subject Hainanese language E228713 entity
Predicate primaryCity P3940 FINISHED
Object Wenchang
Wenchang is a coastal city in northeastern Hainan, China, known as a cultural center and important homeland of many overseas Chinese.
 E804286 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: Wenchang | Statement: [Hainanese language, primaryCity, Wenchang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wenchang
Context triple: [Hainanese language, primaryCity, Wenchang]
  • A. Wanning
    Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
  • B. Xingsha
    Xingsha is a town in Changsha County, Hunan Province, China, known as the modern urban area closest to the famous Mawangdui Han Tombs archaeological site.
  • C. Haikou
    Haikou is the capital and largest city of China’s Hainan Province, known as a key port, commercial hub, and tropical coastal destination.
  • D. Beihai
    Beihai is a coastal city in China's Guangxi Zhuang Autonomous Region, known for its beaches, maritime trade, and the scenic Silver Beach tourist area.
  • E. 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.
  • 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: Wenchang
Triple: [Hainanese language, primaryCity, Wenchang]
Generated description
Wenchang is a coastal city in northeastern Hainan, China, known as a cultural center and important homeland of many overseas Chinese.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wenchang
Target entity description: Wenchang is a coastal city in northeastern Hainan, China, known as a cultural center and important homeland of many overseas Chinese.
  • A. Wanning
    Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
  • B. Xingsha
    Xingsha is a town in Changsha County, Hunan Province, China, known as the modern urban area closest to the famous Mawangdui Han Tombs archaeological site.
  • C. Haikou
    Haikou is the capital and largest city of China’s Hainan Province, known as a key port, commercial hub, and tropical coastal destination.
  • D. Beihai
    Beihai is a coastal city in China's Guangxi Zhuang Autonomous Region, known for its beaches, maritime trade, and the scenic Silver Beach tourist area.
  • E. 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.
  • 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_69ca84730a5081908de282651019bf2f completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd804e278c8190b1f869158075cd52 completed April 1, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d139f7fa90819092e3fbcc62a9e5b9 completed April 4, 2026, 4:19 p.m.
NEDg Description generation batch_69d13c1a73c88190a4308c3246864a5f completed April 4, 2026, 4:28 p.m.
NED2 Entity disambiguation (via description) batch_69d13c8b5d688190871f6830d0bda3ef completed April 4, 2026, 4:30 p.m.
Created at: March 30, 2026, 7:55 p.m.