Triple

T16467541
Position Surface form Disambiguated ID Type / Status
Subject Zhu Zhanji E399973 entity
Predicate spouse P13 FINISHED
Object Empress Hu NE NERFINISHED

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: Empress Hu | Statement: [Zhu Zhanji, spouse, Empress Hu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Empress Hu
Context triple: [Zhu Zhanji, spouse, Empress Hu]
  • A. Empress Hu chosen
    Empress Hu was a Ming dynasty empress consort of the Xuande Emperor, known primarily for her role within the imperial court and as a member of the Chinese imperial harem.
  • B. Empress Zhang
    Empress Zhang was a Ming dynasty empress consort of the Jiajing Emperor, known for her influential yet often turbulent role within the imperial court.
  • C. Empress Zhang
    Empress Zhang was the principal consort and empress of the Ming dynasty Tianqi Emperor, noted for her political influence at court during his reign.
  • D. Empress Zhang
    Empress Zhang was the primary consort of the Hongxi Emperor of the Ming dynasty and served briefly as empress of China in the early 15th century.
  • E. Empress Zhang
    Empress Zhang was the primary consort and empress of the Hongzhi Emperor of the Ming dynasty, known for her political influence and role in the imperial court of late 15th-century China.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32dcd707081908fb7ca91a8c09e0a completed April 18, 2026, 7:07 a.m.
Created at: April 10, 2026, 5:11 a.m.