Triple

T1124048
Position Surface form Disambiguated ID Type / Status
Subject Tampa Bay area E24678 entity
Predicate hasPart P35 FINISHED
Object St. Petersburg E52027 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: [Tampa Bay area, hasPart, St. Petersburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: St. Petersburg
Context triple: [Tampa Bay area, hasPart, St. Petersburg]
  • A. St. Petersburg
    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, Florida chosen
    St. Petersburg, Florida is a coastal city on Florida’s Gulf Coast known for its sunny climate, beaches, and vibrant arts and cultural scene.
  • C. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • D. Samara
    Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
  • E. Petergof
    Petergof is a historic Russian town near Saint Petersburg, renowned for its grand imperial palaces, elaborate fountains, and landscaped parks along the Gulf of Finland.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbd92a8c8190a16e55f3f739010f completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac59a62b9c8190938b3c571cd8ff5f completed March 7, 2026, 5 p.m.
Created at: March 1, 2026, 7:44 p.m.