Triple

T5990428
Position Surface form Disambiguated ID Type / Status
Subject Wuxi E133333 entity
Predicate locatedWestOf P4239 FINISHED
Object Suzhou E107819 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: Suzhou | Statement: [Wuxi, locatedWestOf, Suzhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suzhou
Context triple: [Wuxi, locatedWestOf, Suzhou]
  • A. Suzhou chosen
    Suzhou is a historic and economically significant city in eastern China, renowned for its classical gardens, canals, and silk industry.
  • B. Wuxi
    Wuxi is a major industrial and cultural city in eastern China, located near Lake Tai and known for its manufacturing, canals, and historic gardens.
  • 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. Yangzhou
    Yangzhou is a historic city in eastern China renowned for its canals, gardens, and role as a major cultural and commercial center along the Grand Canal.
  • E. Changshu
    Changshu is a county-level city in Jiangsu Province, eastern China, known for its textile industry, historic sites, and location near Suzhou and Shanghai.
  • 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_69c0087010d081908bb8142342d63330 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04dc8ab648190beb1bc141796894e completed March 22, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1355db96c8190b40b32b8d3a5dbdf completed March 23, 2026, 12:43 p.m.
Created at: March 22, 2026, 4:05 p.m.