Triple

T5990539
Position Surface form Disambiguated ID Type / Status
Subject Huizhou E133336 entity
Predicate historicalName P65 FINISHED
Object Xin'an
Xin'an is the historical name of the region now known as Huizhou in Guangdong, China, reflecting its earlier administrative and cultural identity.
 E563842 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: Xin'an | Statement: [Huizhou, historicalName, Xin'an]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Xin'an
Context triple: [Huizhou, historicalName, Xin'an]
  • 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. Bo'an
    Bo'an is the courtesy name of Wang Yangming, the influential Ming dynasty philosopher, statesman, and Neo-Confucian thinker.
  • C. Yuanxin
    Yuanxin is the given name of Mao Yuanxin, a Chinese political figure known for being the nephew of Mao Zedong and a prominent youth leader during the Cultural Revolution.
  • D. Heqing
    Heqing was an era name used during the Northern Qi dynasty in imperial China to designate a specific reign period.
  • E. 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.
  • 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: Xin'an
Triple: [Huizhou, historicalName, Xin'an]
Generated description
Xin'an is the historical name of the region now known as Huizhou in Guangdong, China, reflecting its earlier administrative and cultural identity.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Xin'an
Target entity description: Xin'an is the historical name of the region now known as Huizhou in Guangdong, China, reflecting its earlier administrative and cultural identity.
  • 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. Bo'an
    Bo'an is the courtesy name of Wang Yangming, the influential Ming dynasty philosopher, statesman, and Neo-Confucian thinker.
  • C. Yuanxin
    Yuanxin is the given name of Mao Yuanxin, a Chinese political figure known for being the nephew of Mao Zedong and a prominent youth leader during the Cultural Revolution.
  • D. Heqing
    Heqing was an era name used during the Northern Qi dynasty in imperial China to designate a specific reign period.
  • E. 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.
  • 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_69c0087010d081908bb8142342d63330 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04dc8ab648190beb1bc141796894e completed March 22, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1135e653481909869094063d31605 completed March 23, 2026, 10:18 a.m.
NEDg Description generation batch_69c113efd9d88190a1ee7bbed4863a11 completed March 23, 2026, 10:20 a.m.
NED2 Entity disambiguation (via description) batch_69c1146097a88190bdd0345da094607e completed March 23, 2026, 10:22 a.m.
Created at: March 22, 2026, 4:05 p.m.