Triple

T3353997
Position Surface form Disambiguated ID Type / Status
Subject Wangfujing station E70562 entity
Predicate nearby P350 FINISHED
Object Wangfujing Street E357863 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: Wangfujing Street | Statement: [Wangfujing station, nearby, Wangfujing Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wangfujing Street
Context triple: [Wangfujing station, nearby, Wangfujing Street]
  • A. Qianmen Street
    Qianmen Street is a famous historic commercial avenue in central Beijing known for its traditional architecture, shops, and cultural landmarks.
  • B. Nanjing Road
    Nanjing Road is one of Shanghai’s most famous and busiest commercial streets, renowned for its shopping, neon lights, and historic significance.
  • C. Shennong Street
    Shennong Street is a historic, well-preserved old street in Tainan, Taiwan, known for its traditional architecture, temples, and vibrant cultural atmosphere.
  • D. Chunxi Road
    Chunxi Road is a bustling commercial and pedestrian street in Chengdu, China, known for its shopping, dining, and vibrant urban atmosphere.
  • E. Wangfujing commercial district chosen
    Wangfujing commercial district is one of Beijing’s most famous and historic shopping streets, known for its large department stores, boutiques, and vibrant pedestrian atmosphere.
  • 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_69ad85a4ef7c8190a29e2bbd6fa454e4 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb24036848190bac779d17dfdce3b completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360a07dec819094b0645d0e2a91da completed March 13, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:13 p.m.