Triple

T4060438
Position Surface form Disambiguated ID Type / Status
Subject Yíhéyuán E86197 entity
Predicate hasPart P35 FINISHED
Object Suzhou Street E86192 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 Street | Statement: [Yíhéyuán, hasPart, Suzhou Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suzhou Street
Context triple: [Yíhéyuán, hasPart, Suzhou Street]
  • A. Suzhou Street chosen
    Suzhou Street is a reconstructed Qing-dynasty style commercial water town within Beijing’s Summer Palace, featuring traditional canalside shops and architecture designed to evoke the historic charm of Suzhou.
  • B. Anfu Road
    Anfu Road is a leafy, boutique-lined street in Shanghai known for its trendy cafés, independent shops, and preserved European-style architecture.
  • C. Emei Street
    Emei Street is a well-known thoroughfare in Taipei’s Ximending district, noted for its dense concentration of shops, eateries, and youth-oriented nightlife.
  • D. Nanjing Road
    Nanjing Road is one of Shanghai’s most famous and busiest commercial streets, renowned for its shopping, neon lights, and historic significance.
  • E. Huashan Road
    Huashan Road is a notable street in Shanghai’s former French Concession, known for its mix of historic architecture, embassies, universities, and cultural venues.
  • 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_69aed93c69208190a4efac0efe3cd69b completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbd32c0c8190bc575974ccf831b3 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562a98c488190a7e77cd46ff998bc completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:38 p.m.