Triple

T8066567
Position Surface form Disambiguated ID Type / Status
Subject Zhuge Liang E188257 entity
Predicate artName P32318 FINISHED
Object Wolong
Wolong is the style name of Zhuge Liang, the famed strategist and statesman of the Three Kingdoms period in Chinese history.
 E709535 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: Wolong | Statement: [Zhuge Liang, artName, Wolong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wolong
Context triple: [Zhuge Liang, artName, Wolong]
  • A. Huanglong
    Huanglong was a historical Chinese era name used during the reign of Eastern Wu ruler Sun Quan in the Three Kingdoms period.
  • B. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • C. Gaotangling
    Gaotangling is the town that serves as the administrative seat and political center of Wangcheng County in Hunan Province, China.
  • D. Passo Giau
    Passo Giau is a high mountain pass in the Italian Dolomites, renowned for its panoramic alpine views and frequent inclusion in major cycling and motorcycling routes.
  • E. Dayong
    Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
  • 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: Wolong
Triple: [Zhuge Liang, artName, Wolong]
Generated description
Wolong is the style name of Zhuge Liang, the famed strategist and statesman of the Three Kingdoms period in Chinese history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wolong
Target entity description: Wolong is the style name of Zhuge Liang, the famed strategist and statesman of the Three Kingdoms period in Chinese history.
  • A. Huanglong
    Huanglong was a historical Chinese era name used during the reign of Eastern Wu ruler Sun Quan in the Three Kingdoms period.
  • B. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • C. Gaotangling
    Gaotangling is the town that serves as the administrative seat and political center of Wangcheng County in Hunan Province, China.
  • D. Passo Giau
    Passo Giau is a high mountain pass in the Italian Dolomites, renowned for its panoramic alpine views and frequent inclusion in major cycling and motorcycling routes.
  • E. Dayong
    Dayong is the former name of the city now known as Zhangjiajie in Hunan Province, China, famed for its dramatic sandstone pillar landscapes.
  • 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_69ca82b42674819086840efea12478e5 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ff75d208190b7c53d2fe55878ac completed March 31, 2026, 3:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63e1ed44819083ed9db6c9d7b0fd completed April 1, 2026, 12:16 a.m.
NEDg Description generation batch_69cc651c5f788190908c6d84c58cba0f completed April 1, 2026, 12:21 a.m.
NED2 Entity disambiguation (via description) batch_69cc6649d2348190996802140b455348 completed April 1, 2026, 12:26 a.m.
Created at: March 30, 2026, 5:26 p.m.