Triple

T21606501
Position Surface form Disambiguated ID Type / Status
Subject Osip Bove E533187 entity
Predicate workedOn P3 FINISHED
Object Theatre Square in Moscow NE NERFINISHED

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: Theatre Square in Moscow | Statement: [Osip Bove, workedOn, Theatre Square in Moscow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Theatre Square in Moscow
Context triple: [Osip Bove, workedOn, Theatre Square in Moscow]
  • A. Theatre Square, Moscow chosen
    Theatre Square in Moscow is a historic central square renowned as a cultural hub, surrounded by landmark institutions including the Bolshoi Theatre.
  • B. Lubyanka Square, Moscow
    Lubyanka Square, Moscow is a central Moscow square historically known as the site of Russia’s main security service headquarters and the former KGB prison.
  • C. Theatre Square, Saint Petersburg
    Theatre Square in Saint Petersburg is a historic city square renowned as a cultural hub, surrounded by major landmarks including the Mariinsky Theatre.
  • D. Kızılay Square
    Kızılay Square is a major central square and transportation hub in Ankara, Turkey, known as one of the city's main commercial and social gathering points.
  • E. Lenin Square
    Lenin Square was the Soviet-era central public square in Bishkek, Kyrgyzstan, later renamed Ala-Too Square after the country’s independence.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46364608190a337dc8720dc2a35 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef17e5783481909db36c388f3ae227 completed April 27, 2026, 8:01 a.m.
Created at: April 16, 2026, 6:33 p.m.