Triple

T36135
Position Surface form Disambiguated ID Type / Status
Subject Los Angeles E715 entity
Predicate hasSisterCity P919 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: [Los Angeles, hasSisterCity, St. Petersburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: St. Petersburg
Context triple: [Los Angeles, hasSisterCity, 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. Moscow
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • C. Fairbanks
    Fairbanks is a surname most famously associated with Douglas Fairbanks, a pioneering American silent film actor, producer, and one of the founders of United Artists.
  • D. Miami
    Miami is a major coastal city in southeastern Florida known for its vibrant nightlife, diverse culture, and role as a global center for finance, tourism, and international trade.
  • E. New Orleans
    New Orleans is a historic port city in southeastern Louisiana known for its vibrant jazz music, Creole cuisine, and distinctive French and Spanish-influenced architecture.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ec1ef5481909daf99654dfa3f57 completed Feb. 28, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a26c15db808190b8d66206a4ed1085 completed Feb. 28, 2026, 4:16 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.