Triple

T2343100
Position Surface form Disambiguated ID Type / Status
Subject Mariinsky Theatre E45069 entity
Predicate architect P184 FINISHED
Object Albert Cavos E45068 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: Albert Cavos | Statement: [Mariinsky Theatre, architect, Albert Cavos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albert Cavos
Context triple: [Mariinsky Theatre, architect, Albert Cavos]
  • A. Albert Cavos chosen
    Albert Cavos was a 19th-century Russian architect best known for designing major imperial theaters, including the Mariinsky Theatre in Saint Petersburg.
  • B. Matthias Bartoli
    Matthias Bartoli is a linguist known for his work documenting and studying the now-extinct Dalmatian language.
  • C. Patrick de Carolis
    Patrick de Carolis is a French journalist and television executive who became the mayor of Arles.
  • D. Bruno Siciliano
    Bruno Siciliano is an Italian roboticist and professor renowned for his influential research, leadership, and educational contributions in the field of robotics and automation.
  • E. Paul Piana
    Paul Piana is an American rock climber best known for pioneering the first free ascent of El Capitan’s Salathé Wall in Yosemite, a landmark achievement in big-wall free climbing.
  • 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_69a88917935081909b755dbf38e81024 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6ae33e881909a81a0c0def59059 completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf2ae2c4819083403236e27d4b5e completed March 9, 2026, 12:38 p.m.
Created at: March 4, 2026, 7:52 p.m.