Triple

T5747270
Position Surface form Disambiguated ID Type / Status
Subject The Nose E126765 entity
Predicate setting P1957 FINISHED
Object Saint Petersburg E916 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: Saint Petersburg | Statement: [The Nose, setting, Saint Petersburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint Petersburg
Context triple: [The Nose, setting, Saint Petersburg]
  • A. Saint Petersburg Federal City
    Saint Petersburg Federal City is a major Russian federal subject centered on the historic city of Saint Petersburg, a key cultural, scientific, and industrial hub in northwestern Russia.
  • B. Saint Petersburg, Russian Empire
    Saint Petersburg, Russian Empire was the imperial capital and cultural center of Russia, renowned for its grand architecture, canals, and role as a major European metropolis.
  • C. St. Petersburg
    St. Petersburg is the fictional Mississippi River town that serves as the central backdrop for Mark Twain’s classic novel "The Adventures of Tom Sawyer."
  • D. St. Petersburg chosen
    St. Petersburg is a major Russian port city on the Baltic Sea, renowned for its imperial architecture, cultural heritage, and role as a historic capital of Russia.
  • E. Ekaterinodar
    Ekaterinodar, now known as Krasnodar, was a major city in southern Russia that served as an important political and military center in the Kuban region.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02885b0288190835809681a364b1f completed March 22, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07d65dafc819083b60cbff2031819 completed March 22, 2026, 11:38 p.m.
Created at: March 22, 2026, 3:48 p.m.