Triple

T8531027
Position Surface form Disambiguated ID Type / Status
Subject State of Wei E201948 entity
Predicate capital P234 FINISHED
Object Kaifeng E131801 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: Kaifeng | Statement: [State of Wei, capital, Kaifeng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaifeng
Context triple: [State of Wei, capital, Kaifeng]
  • A. Kaifeng chosen
    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. 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.
  • C. Zhoukou
    Zhoukou is a prefecture-level city in eastern Henan Province, China, known as an important agricultural and transportation hub with historical and cultural significance.
  • D. Zhengzhou
    Zhengzhou is a major city in central China that serves as the capital of Henan Province and an important national transportation and industrial hub.
  • E. Xuchang
    Xuchang is a historically significant city in central China, known as a former capital during the Three Kingdoms period and now an important industrial and transportation hub.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe67546248190b359c845c0161ad3 completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d09b22da4c81909aacc9c4a6af379c completed April 4, 2026, 5:01 a.m.
Created at: March 30, 2026, 6:17 p.m.