Triple

T963044
Position Surface form Disambiguated ID Type / Status
Subject Lenin Mausoleum E20776 entity
Predicate nearby P350 FINISHED
Object GUM department store E99515 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: GUM department store | Statement: [Lenin Mausoleum, nearby, GUM department store]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GUM department store
Context triple: [Lenin Mausoleum, nearby, GUM department store]
  • A. GUM department store chosen
    GUM department store is a historic, glass-roofed shopping arcade in central Moscow known for its grand architecture and luxury retail outlets.
  • B. Passage department store
    Passage department store is a historic and elegant shopping arcade in Saint Petersburg, Russia, renowned for its 19th-century architecture and upscale boutiques.
  • C. Bergdorf Goodman store
    Bergdorf Goodman store is a luxury department store in New York City renowned for its high-end fashion, designer brands, and iconic window displays.
  • D. Bijenkorf department store
    The Bijenkorf department store is a flagship luxury retail store in Amsterdam known for its high-end fashion, design, and prominent location in the city center.
  • E. Shibuya 109
    Shibuya 109 is a famous multi-story fashion shopping mall in Tokyo known as a trendsetting hub for youth and street fashion.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b416cf4c8190bd685227db25fb53 completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac11a6107481909b152291a73958d3 completed March 7, 2026, 11:53 a.m.
Created at: March 1, 2026, 7:40 p.m.