Triple

T5925530
Position Surface form Disambiguated ID Type / Status
Subject Kaifeng E131801 entity
Predicate historicalName P65 FINISHED
Object Bianjing E559814 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: Bianjing | Statement: [Kaifeng, historicalName, Bianjing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bianjing
Context triple: [Kaifeng, historicalName, Bianjing]
  • A. Kaifeng
    Kaifeng is an ancient city in eastern Henan, China, historically significant as a former capital of several Chinese dynasties and a major cultural and economic center.
  • B. Zhongdu
    Zhongdu was the historical capital city of the Jurchen-led Jin dynasty in northern China, located in what is now part of modern Beijing.
  • C. Luoyang
    Luoyang is one of China’s oldest and most historically significant cities, renowned as an ancient imperial capital and cultural center along the Yellow River.
  • D. Dongjing chosen
    Dongjing is the historical name for Kaifeng when it served as the capital of the Northern Song dynasty in China.
  • E. Shangjing
    Shangjing was the principal early capital city of China’s Jurchen-led Jin dynasty, serving as a key political and administrative center in northeastern China.
  • 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_69c0085b75e88190a632f9691f9da48b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03852806c81908ba726c16adf3358 completed March 22, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c108186c64819088c21e9b5408d5f1 completed March 23, 2026, 9:30 a.m.
Created at: March 22, 2026, 4 p.m.