Triple

T10057277
Position Surface form Disambiguated ID Type / Status
Subject An Lushan Rebellion E208893 entity
Predicate leader P981 FINISHED
Object An Lushan E782721 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: An Lushan | Statement: [An Lushan Rebellion, leader, An Lushan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: An Lushan
Context triple: [An Lushan Rebellion, leader, An Lushan]
  • A. An Lushan chosen
    An Lushan was a Tang dynasty general of Sogdian and Turkic origin who led the devastating An Lushan Rebellion (755–763), which severely weakened the Tang Empire.
  • B. Mount Wangwu
    Mount Wangwu is a renowned scenic mountain area in China, celebrated for its dramatic landscapes, cultural legends, and historical significance within the Taihang mountain range.
  • C. Pan Shu
    Pan Shu was an imperial consort of the Eastern Wu state during China’s Three Kingdoms period and the mother of Emperor Sun Liang.
  • D. Tudigong
    Tudigong is a widely venerated Chinese earth god and local tutelary deity associated with protecting land, villages, and community welfare.
  • E. Ma Sichun
    Ma Sichun is a Chinese actress known for her acclaimed film and television roles, including winning the Golden Horse Award for Best Leading Actress.
  • 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_69ca836094408190a36a1ea7e9a86fcd completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcfaf7700819084dedf7b63e789c1 completed April 2, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a5258788190a4ecdefa5b520609 completed April 5, 2026, 5:22 p.m.
Created at: March 30, 2026, 8:57 p.m.