Triple

T1326428
Position Surface form Disambiguated ID Type / Status
Subject Tampa International Airport E28338 entity
Predicate serves P98 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 International Airport, serves, St. Petersburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: St. Petersburg
Context triple: [Tampa International Airport, serves, 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. 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.
  • D. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • E. Samara
    Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c19fd2648190932a85eacb3e7ec4 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62764d88190b7d1fca10835f560 completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:55 p.m.