Triple

T5134582
Position Surface form Disambiguated ID Type / Status
Subject Fengtian E115788 entity
Predicate romanizationVariant P5923 FINISHED
Object Feng-tien-fu E496849 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: Feng-tien-fu | Statement: [Fengtian, romanizationVariant, Feng-tien-fu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Feng-tien-fu
Context triple: [Fengtian, romanizationVariant, Feng-tien-fu]
  • A. Feng-tien chosen
    Feng-tien is an older romanized form of the name Fengtian, historically used for the city now known as Shenyang in northeastern China.
  • B. Foxiangge
    Foxiangge is the Tower of Buddhist Incense, a prominent multi-story pavilion and iconic landmark within Beijing’s Summer Palace complex.
  • C. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • D. Hsia-men
    Hsia-men is an older romanized form of the name for Xiamen, a major port city on the southeast coast of China in Fujian Province.
  • E. Feng
    Feng is a Chinese surname borne by various notable figures in Chinese history and culture.
  • 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_69bd44459a988190a772a5c2ec6a1965 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd784e306081908dd8317227227807 completed March 20, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfdd965c8190adda020ead81bd05 completed March 21, 2026, 5:05 p.m.
Created at: March 20, 2026, 1:43 p.m.