Triple

T13951239
Position Surface form Disambiguated ID Type / Status
Subject Liyang E335527 entity
Predicate romanization P2508 FINISHED
Object Lìyáng
Lìyáng is a Chinese place name rendered in pinyin, most commonly referring to a county-level city in Jiangsu Province, China.
E1071511 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: Lìyáng | Statement: [Liyang, romanization, Lìyáng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lìyáng
Context triple: [Liyang, romanization, Lìyáng]
  • A. Luòyáng
    Luòyáng is an ancient Chinese city in Henan Province that served as the capital for multiple dynasties and is renowned as one of the cradles of Chinese civilization.
  • B. Liúyáng
    Liúyáng is the Hanyu Pinyin romanization of the Chinese city name Liuyang, located in Hunan Province, China.
  • C. Lüliang
    Lüliang is a prefecture-level city in western Shanxi Province, China, known for its mountainous terrain and significant coal and energy resources.
  • D. Pingcheng
    Pingcheng was an important ancient Chinese city that served as the early capital of the Northern Wei dynasty, located near present-day Datong in Shanxi Province.
  • E. Xianyang
    Xianyang was the capital city of the Qin dynasty and a major political and cultural center in ancient China.
  • 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: Lìyáng
Triple: [Liyang, romanization, Lìyáng]
Generated description
Lìyáng is a Chinese place name rendered in pinyin, most commonly referring to a county-level city in Jiangsu Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lìyáng
Target entity description: Lìyáng is a Chinese place name rendered in pinyin, most commonly referring to a county-level city in Jiangsu Province, China.
  • A. Luòyáng
    Luòyáng is an ancient Chinese city in Henan Province that served as the capital for multiple dynasties and is renowned as one of the cradles of Chinese civilization.
  • B. Liúyáng
    Liúyáng is the Hanyu Pinyin romanization of the Chinese city name Liuyang, located in Hunan Province, China.
  • C. Lüliang
    Lüliang is a prefecture-level city in western Shanxi Province, China, known for its mountainous terrain and significant coal and energy resources.
  • D. Pingcheng
    Pingcheng was an important ancient Chinese city that served as the early capital of the Northern Wei dynasty, located near present-day Datong in Shanxi Province.
  • E. Xianyang
    Xianyang was the capital city of the Qin dynasty and a major political and cultural center in ancient China.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e131c608190b4ffdbada24a3208 completed April 14, 2026, 12:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1cca84881909c7733bbc2609eea completed May 6, 2026, 8:17 p.m.
NEDg Description generation batch_69fba6af4ed881908cb4b79cfa40977c completed May 6, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_69fba71a91fc8190b24185994673b33b completed May 6, 2026, 8:39 p.m.
Created at: April 9, 2026, 10:17 p.m.