Triple

T3031469
Position Surface form Disambiguated ID Type / Status
Subject Courtrai E82904 entity
Predicate twinCity P1072 FINISHED
Object Wuxi E133333 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: Wuxi | Statement: [Courtrai, twinCity, Wuxi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wuxi
Context triple: [Courtrai, twinCity, Wuxi]
  • A. Wuxi chosen
    Wuxi is a major industrial and cultural city in eastern China, located near Lake Tai and known for its manufacturing, canals, and historic gardens.
  • B. Changzhou
    Changzhou is a major industrial and commercial city in Jiangsu Province, eastern China, known for its manufacturing base and location along the Yangtze River.
  • C. Zhenjiang
    Zhenjiang is a historic port city in eastern China known for its strategic location on the Yangtze River and its rich cultural and culinary heritage.
  • D. Nantong
    Nantong is a coastal city in eastern China known for its textile industry, river and sea ports, and location on the northern bank of the Yangtze River opposite Shanghai.
  • E. Suzhou
    Suzhou is a historic and economically significant city in eastern China, renowned for its classical gardens, canals, and silk industry.
  • 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_69ad8b21a62881908ec5dd4fba4a187c completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9aee2fec81908116939a8d773fc4 completed March 8, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b488165eb48190ae5b080862919caf completed March 13, 2026, 9:56 p.m.
Created at: March 8, 2026, 3:01 p.m.