Triple

T20747351
Position Surface form Disambiguated ID Type / Status
Subject Mount Jiuhua E510619 entity
Predicate ChineseName P744 FINISHED
Object 九华山 — NE NERFINISHED

How this triple was built (3 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: 九华山 | Statement: [Mount Jiuhua, ChineseName, 九华山]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 九华山
Context triple: [Mount Jiuhua, ChineseName, 九华山]
  • A. 光明顶
    光明顶是位于安徽黄山风景区的一座著名山峰，以壮丽的日出云海景观和在金庸武侠小说《倚天屠龙记》中的重要地位而闻名。
  • B. 武当山
    武当山是位于中国湖北省的著名道教名山和世界文化遗产，以其古建筑群和武当武术而闻名。
  • C. 五台山
    五台山是位于中国山西省、以文殊菩萨道场著称的佛教名山和世界文化遗产。
  • D. 天台山
    天台山是位于中国浙江省的著名山岳与佛教天台宗发源地，以秀丽的自然风光和深厚的宗教文化闻名。
  • E. 采石矶
    采石矶是位于中国安徽省长江岸边、以奇岩险峻和与李白等诗人相关的历史文化典故闻名的著名风景名胜。
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 九华山
Target entity description: 九华山是中国安徽省著名的佛教名山之一，以地藏菩萨道场和秀丽的山水风光闻名。
  • A. 光明顶
    光明顶是位于安徽黄山风景区的一座著名山峰，以壮丽的日出云海景观和在金庸武侠小说《倚天屠龙记》中的重要地位而闻名。
  • B. 武当山
    武当山是位于中国湖北省的著名道教名山和世界文化遗产，以其古建筑群和武当武术而闻名。
  • C. 五台山
    五台山是位于中国山西省、以文殊菩萨道场著称的佛教名山和世界文化遗产。
  • D. 天台山
    天台山是位于中国浙江省的著名山岳与佛教天台宗发源地，以秀丽的自然风光和深厚的宗教文化闻名。
  • E. 采石矶
    采石矶是位于中国安徽省长江岸边、以奇岩险峻和与李白等诗人相关的历史文化典故闻名的著名风景名胜。
  • F. None of above. chosen

Provenance (2 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_69e0b4c845e88190b4c5f3ae79291182 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c226fbf881909794eff3ee9e206b completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:33 p.m.