Triple

T8681651
Position Surface form Disambiguated ID Type / Status
Subject Feng E206051 entity
Predicate transliteratesCharacter P84461 FINISHED
Object E751169 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: 馮 | Statement: [Feng, transliteratesCharacter, 馮]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 馮
Context triple: [Feng, transliteratesCharacter, 馮]
  • A. chosen
    冯 is a common Chinese surname with ancient origins, used by many notable historical and contemporary figures.
  • B.
    陳 is a common Chinese surname and character with historical roots, widely used across Chinese-speaking communities and often romanized as "Chan," "Chen," or similar variants.
  • C. Fu Cong
    Fu Cong is a Chinese diplomat who serves as the Permanent Representative of the People’s Republic of China to the United Nations.
  • D. Feng
    Feng is a Chinese surname borne by various notable figures in Chinese history and culture.
  • E. 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.
  • 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_69ca835379688190aa06b9d98e684d58 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5c2e9c688190aceefaa2c3b7d7bd completed March 31, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf287f05748190b41c606eaae5d0b7 completed April 3, 2026, 2:39 a.m.
Created at: March 30, 2026, 6:32 p.m.