Triple

T19885720
Position Surface form Disambiguated ID Type / Status
Subject Gusu District E477894 entity
Predicate contains P35 FINISHED
Object Suzhou old town NE NERFINISHED

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 old town | Statement: [Gusu District, contains, Suzhou old town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suzhou old town
Context triple: [Gusu District, contains, Suzhou old town]
  • A. Suzhou chosen
    Suzhou is a historic and economically significant city in eastern China, renowned for its classical gardens, canals, and silk industry.
  • B. Songjiang Old Town
    Songjiang Old Town is a historic district in Shanghai known for its ancient architecture, traditional waterways, and well-preserved cultural heritage.
  • C. Wuzhen
    Wuzhen is a historic water town in eastern China known for its ancient canals, traditional architecture, and cultural tourism.
  • D. Jiangnan water towns
    Jiangnan water towns are a group of historic canal-based settlements in the Yangtze River Delta, famed for their traditional architecture, stone bridges, and picturesque waterways.
  • E. Zhouzhuang
    Zhouzhuang is one of China’s most famous ancient water towns, renowned for its well-preserved canals, stone bridges, and traditional Jiangnan architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65909fe0481908e22b60d04fe2b11 completed April 20, 2026, 4:49 p.m.
Created at: April 10, 2026, 1:52 p.m.