Triple

T1695724
Position Surface form Disambiguated ID Type / Status
Subject Shiyan E36652 entity
Predicate romanization P2508 FINISHED
Object Shíyàn
Shíyàn is the Hanyu Pinyin romanization of the Chinese city name Shiyan, located in Hubei Province, China.
E213309 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: Shíyàn | Statement: [Shiyan, romanization, Shíyàn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shíyàn
Context triple: [Shiyan, romanization, Shíyàn]
  • A. Shëngjin
    Shëngjin is a coastal town and port in northwestern Albania on the Adriatic Sea, historically significant for its strategic maritime position.
  • B. Chongxin
    Chongxin is the Chinese given name of Joe Tsai, the Taiwanese-Canadian co-founder and executive vice chairman of Alibaba Group.
  • C. Xinjing
    Xinjing was the capital city of the Japanese puppet state of Manchukuo in northeastern China during the 1930s and early 1940s.
  • D. Jianye
    Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
  • E. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • 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: Shíyàn
Triple: [Shiyan, romanization, Shíyàn]
Generated description
Shíyàn is the Hanyu Pinyin romanization of the Chinese city name Shiyan, located in Hubei Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Shíyàn
Target entity description: Shíyàn is the Hanyu Pinyin romanization of the Chinese city name Shiyan, located in Hubei Province, China.
  • A. Shëngjin
    Shëngjin is a coastal town and port in northwestern Albania on the Adriatic Sea, historically significant for its strategic maritime position.
  • B. Chongxin
    Chongxin is the Chinese given name of Joe Tsai, the Taiwanese-Canadian co-founder and executive vice chairman of Alibaba Group.
  • C. Xinjing
    Xinjing was the capital city of the Japanese puppet state of Manchukuo in northeastern China during the 1930s and early 1940s.
  • D. Jianye
    Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
  • E. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b645a081909dafdf7a32f2a389 completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeac88e488190aeb6e7a1063405b7 completed March 8, 2026, 9:31 p.m.
NEDg Description generation batch_69adeb8a0a64819087e4505089e93093 completed March 8, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69adec6fcaac8190b43d0cd1aa613c95 completed March 8, 2026, 9:38 p.m.
Created at: March 4, 2026, 7:30 p.m.