Triple

T19839703
Position Surface form Disambiguated ID Type / Status
Subject Fu E476693 entity
Predicate hasVariantTransliteration P5923 FINISHED
Object Fu (Wade–Giles) 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: Fu (Wade–Giles) | Statement: [Fu, hasVariantTransliteration, Fu (Wade–Giles)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fu (Wade–Giles)
Context triple: [Fu, hasVariantTransliteration, Fu (Wade–Giles)]
  • A. Wade–Giles chosen
    Wade–Giles is a historical system for romanizing Mandarin Chinese that was widely used in the English-speaking world before being largely replaced by Pinyin.
  • B. Yuanfu
    Yuanfu was the courtesy name of Lin Zexu, the prominent Qing dynasty official known for his role in suppressing the opium trade and helping trigger the First Opium War.
  • C. Furu Wei
    Furu Wei is a Chinese computer scientist and AI researcher known for his influential work in natural language processing and document understanding at Microsoft Research.
  • D. Feng
    Feng was an early capital city of the Zhou dynasty in ancient China, serving as a key political and cultural center before later relocations.
  • E. Feng
    Feng is the flamboyant and villainous crime lord and ping-pong master who serves as the main antagonist in the comedy film "Balls of Fury."
  • 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65804be608190b49e110c3bf381bc completed April 20, 2026, 4:44 p.m.
Created at: April 10, 2026, 1:50 p.m.