Triple

T11886757
Position Surface form Disambiguated ID Type / Status
Subject Catherine Palace E282803 entity
Predicate locatedIn P40 FINISHED
Object Tsarskoye Selo E66671 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: Tsarskoye Selo | Statement: [Catherine Palace, locatedIn, Tsarskoye Selo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tsarskoye Selo
Context triple: [Catherine Palace, locatedIn, Tsarskoye Selo]
  • A. Tsarskoye Selo chosen
    Tsarskoye Selo is a former imperial residence near Saint Petersburg, Russia, famed for its opulent palaces, landscaped parks, and role as a cultural and historical center of the Russian Empire.
  • B. Gatchina
    Gatchina is a historic Russian town near Saint Petersburg, known for its imperial palace complex and long association with the Romanov dynasty.
  • C. Pavlovsk
    Pavlovsk is a historic Russian town near Saint Petersburg, best known for its imperial palace and landscaped park that exemplify neoclassical architecture and design.
  • D. Pavlovsk
    Pavlovsk is a town in southwestern Russia known as a local administrative and cultural center within Voronezh Oblast.
  • E. Tsaritsyno
    Tsaritsyno is a Moscow Metro station named after the nearby historic Tsaritsyno district and palace complex in southern Moscow.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d3a13370819086386fecb99e4f0b completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f281fc9660819081fc2fd1f44440d8 completed April 29, 2026, 10:11 p.m.
Created at: April 8, 2026, 9:44 p.m.