Triple

T3489239
Position Surface form Disambiguated ID Type / Status
Subject Fuxingmen station E73684 entity
Predicate near P350 FINISHED
Object Xidan commercial district E350198 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: Xidan commercial district | Statement: [Fuxingmen station, near, Xidan commercial district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xidan commercial district
Context triple: [Fuxingmen station, near, Xidan commercial district]
  • A. Xidan shopping district chosen
    Xidan shopping district is a major commercial and entertainment hub in central Beijing, known for its large malls, department stores, and vibrant youth culture.
  • B. Tenjin commercial district
    The Tenjin commercial district is Fukuoka’s central downtown hub, renowned for its dense concentration of shopping malls, department stores, dining, and entertainment venues.
  • C. Dongzhimen commercial area
    Dongzhimen commercial area is a major shopping and business district in Beijing known for its retail centers, restaurants, and transport connectivity.
  • D. Xidan station
    Xidan station is a major interchange stop on the Beijing Subway serving the busy commercial and shopping district of Xidan in central Beijing.
  • E. Ginza
    Ginza is a famous upscale shopping, dining, and entertainment district in central Tokyo known for its luxury boutiques, department stores, and vibrant nightlife.
  • 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_69ad85cca8d4819088494e9f3340fab5 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbb92b3ac8190b8675f5a5e9d4408 completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373bb0e00819087899a394f50295d completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:18 p.m.