Triple

T259435
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Taiwan E5508 entity
Predicate seeCity P3207 FINISHED
Object Taipei E14412 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: Taipei | Statement: [Diocese of Taiwan, seeCity, Taipei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taipei
Context triple: [Diocese of Taiwan, seeCity, Taipei]
  • A. Taipei, Taiwan chosen
    Taipei, Taiwan is the capital and largest city of Taiwan, known as a major political, economic, and cultural center in East Asia.
  • B. Shanghai
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • C. Beijing
    Beijing is the capital city of China, a major political, cultural, and economic center known for its rich history and rapid modern development.
  • D. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • E. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d71a10c8190894c86e7a67c5974 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3837622cc819096df20695413b5c0 completed March 1, 2026, 12:08 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.