Triple

T19235529
Position Surface form Disambiguated ID Type / Status
Subject Ivan Desny E480981 entity
Predicate placeOfBirth P1 FINISHED
Object Peking 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: Peking | Statement: [Ivan Desny, placeOfBirth, Peking]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peking
Context triple: [Ivan Desny, placeOfBirth, Peking]
  • A. Pekin
    Pekin is a small hamlet in Niagara County, New York, known historically as a stop on the Underground Railroad.
  • B. Beijing chosen
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • C. Tiāntán
    Tiāntán is the Chinese pinyin name for the Temple of Heaven, a historic imperial religious complex in Beijing where Ming and Qing dynasty emperors performed annual ceremonies to pray for good harvests.
  • D. Yuan Dadu
    Yuan Dadu was the capital city of the Yuan dynasty in China, located on the site of present-day Beijing and serving as a major political and cultural center of the Mongol-ruled empire.
  • E. Hangtou
    Hangtou is a town in Shanghai, China, known as the southern terminus of the Shanghai Metro’s Line 18.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5faec6d0c8190b90cb1bb3160a847 completed April 20, 2026, 10:07 a.m.
Created at: April 10, 2026, 1:26 p.m.