Triple

T8326734
Position Surface form Disambiguated ID Type / Status
Subject Foshan E194972 entity
Predicate romanization P2508 FINISHED
Object Fóshān
Fóshān is the standard pinyin romanization of the name of the major industrial and cultural city of Foshan in Guangdong Province, China.
 E725219 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: Fóshān | Statement: [Foshan, romanization, Fóshān]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fóshān
Context triple: [Foshan, romanization, Fóshān]
  • A. Xin’an
    Xin’an is the former name of Nantou, a historic town in Shenzhen, China, that once served as an important administrative and commercial center in the region.
  • B. Shekou
    Shekou is a coastal district in Shenzhen, China, known as a major transportation and commercial hub with significant port facilities and expatriate communities.
  • C. Lüshun
    Lüshun is a strategically important port city in northeastern China, historically known as Port Arthur and noted for its role in several major conflicts.
  • D. Fenghua
    Fenghua is a county-level city in Zhejiang Province, China, known as the hometown of former Chinese leader Chiang Kai-shek.
  • E. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • 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: Fóshān
Triple: [Foshan, romanization, Fóshān]
Generated description
Fóshān is the standard pinyin romanization of the name of the major industrial and cultural city of Foshan in Guangdong Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fóshān
Target entity description: Fóshān is the standard pinyin romanization of the name of the major industrial and cultural city of Foshan in Guangdong Province, China.
  • A. Xin’an
    Xin’an is the former name of Nantou, a historic town in Shenzhen, China, that once served as an important administrative and commercial center in the region.
  • B. Shekou
    Shekou is a coastal district in Shenzhen, China, known as a major transportation and commercial hub with significant port facilities and expatriate communities.
  • C. Lüshun
    Lüshun is a strategically important port city in northeastern China, historically known as Port Arthur and noted for its role in several major conflicts.
  • D. Fenghua
    Fenghua is a county-level city in Zhejiang Province, China, known as the hometown of former Chinese leader Chiang Kai-shek.
  • E. Yuncheng
    Yuncheng is a major city in southern Shanxi Province, China, known for its historical sites and role as a regional transportation and economic hub.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f80ed288190b300e18b9bc58824 completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95b92708819097795498f9ebcdfc completed April 1, 2026, 10:01 p.m.
NEDg Description generation batch_69cdab60ec308190a9001f9235e556b4 completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2e3457c8190a2d0cb6eeb81c9ef completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:56 p.m.