Triple

T2591818
Position Surface form Disambiguated ID Type / Status
Subject Lushan Conference of 1959 E58138 entity
Predicate location P40 FINISHED
Object Lushan E205470 NE FINISHED

How this triple was built (2 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: Lushan | Statement: [Lushan Conference of 1959, location, Lushan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lushan
Context triple: [Lushan Conference of 1959, location, Lushan]
  • A. Lushan Mountain chosen
    Lushan Mountain is a famous scenic and cultural mountain area in southeastern China, renowned for its dramatic cliffs, misty landscapes, and historical significance as a UNESCO World Heritage Site.
  • B. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • C. Wuzhishan
    Wuzhishan is a county-level city in central Hainan, China, known for its mountainous terrain and tropical rainforest environment.
  • D. Zijincheng
    Zijincheng is the Chinese name for the Forbidden City, the vast imperial palace complex in central Beijing that served as the home of emperors and the political heart of China for nearly five centuries.
  • E. Xishan
    Xishan is the given name of Yan Xishan, a prominent Chinese warlord and political leader active in Shanxi during the early 20th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd425851c819088db89713c07056f completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af6589a9c48190b16b5b7959096aab completed March 10, 2026, 12:27 a.m.
Created at: March 6, 2026, 9:49 p.m.