Triple

T7377309
Position Surface form Disambiguated ID Type / Status
Subject Yueyang E170158 entity
Predicate hasCountyLevelCity P27799 FINISHED
Object Linxiang
Linxiang is a county-level city administered by Yueyang in Hunan Province, China, known for its location near the Yangtze River and its regional agricultural and industrial activities.
 E660002 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: Linxiang | Statement: [Yueyang, hasCountyLevelCity, Linxiang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Linxiang
Context triple: [Yueyang, hasCountyLevelCity, Linxiang]
  • A. Yuxiang
    Yuxiang is a Chinese given name notably borne by the early 20th-century warlord and military leader Feng Yuxiang.
  • B. Huaxiang
    Huaxiang is a subdistrict-level area within Beijing’s Fengtai District, known primarily as a residential and urban community zone.
  • C. Luzhi
    Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
  • D. Xiaochang
    Xiaochang is a county in Hubei Province, China, known historically as a rural mission and teaching post where figures like Eric Liddell worked.
  • E. Longchang
    Longchang was a Chinese era name used during the Northern Qi dynasty to designate a specific reign period.
  • 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: Linxiang
Triple: [Yueyang, hasCountyLevelCity, Linxiang]
Generated description
Linxiang is a county-level city administered by Yueyang in Hunan Province, China, known for its location near the Yangtze River and its regional agricultural and industrial activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Linxiang
Target entity description: Linxiang is a county-level city administered by Yueyang in Hunan Province, China, known for its location near the Yangtze River and its regional agricultural and industrial activities.
  • A. Yuxiang
    Yuxiang is a Chinese given name notably borne by the early 20th-century warlord and military leader Feng Yuxiang.
  • B. Huaxiang
    Huaxiang is a subdistrict-level area within Beijing’s Fengtai District, known primarily as a residential and urban community zone.
  • C. Luzhi
    Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
  • D. Xiaochang
    Xiaochang is a county in Hubei Province, China, known historically as a rural mission and teaching post where figures like Eric Liddell worked.
  • E. Longchang
    Longchang was a Chinese era name used during the Northern Qi dynasty to designate a specific reign period.
  • 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_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1aa12888190b81e37b9fcd2adc0 completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802d15a8481908e43701459607276 completed March 28, 2026, 4:33 p.m.
NEDg Description generation batch_69c803ad72308190a9640f2fb043daab completed March 28, 2026, 4:37 p.m.
NED2 Entity disambiguation (via description) batch_69c8043121988190b7c9ea0f786296c2 completed March 28, 2026, 4:39 p.m.
Created at: March 27, 2026, 3:07 p.m.