Triple

T5240436
Position Surface form Disambiguated ID Type / Status
Subject Sonya E118325 entity
Predicate setting P1957 FINISHED
Object St. 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: St. Petersburg | Statement: [Sonya, setting, St. Petersburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: St. Petersburg
Context triple: [Sonya, setting, St. Petersburg]
  • A. 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.
  • B. 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."
  • C. St. Petersburg, Florida
    St. Petersburg, Florida is a coastal city on Florida’s Gulf Coast known for its sunny climate, beaches, and vibrant arts and cultural scene.
  • D. 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.
  • E. Port of St. Petersburg
    The Port of St. Petersburg is a small municipal marina and recreational port on Florida’s Gulf Coast that primarily serves private vessels, research ships, and local tourism rather than large commercial shipping.
  • 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_69bd4467db0881909b3b0982df32cc8f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b2a52fc8190a22631e1853c74a3 completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef8278cb88190aa1e0a42d2f8fe8d completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:49 p.m.