Triple

T8391960
Position Surface form Disambiguated ID Type / Status
Subject Ekaterina Gordeeva E197963 entity
Predicate givenName P17 FINISHED
Object Ekaterina E405551 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: Ekaterina | Statement: [Ekaterina Gordeeva, givenName, Ekaterina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ekaterina
Context triple: [Ekaterina Gordeeva, givenName, Ekaterina]
  • A. Yekaterina chosen
    Yekaterina is a common Russian female given name, equivalent to Catherine in English.
  • B. Anna Karlovna
    Anna Karlovna is an alternative name for Anna Leopoldovna, the 18th-century Russian regent who ruled on behalf of the infant Emperor Ivan VI.
  • C. Tsesarevna of Russia
    Tsesarevna of Russia was the title traditionally borne by the daughters or female-line heirs of a Russian tsar, denoting their status as imperial princesses in the Russian monarchy.
  • D. Natalia Petrovna of Russia
    Natalia Petrovna of Russia was a Russian noblewoman of the imperial era, known as a member of the extended Romanov family.
  • E. Anna Ivanovna of Russia
    Anna Ivanovna of Russia was Empress of Russia from 1730 to 1740, known for her autocratic rule, reliance on Baltic German advisers, and the continuation of Peter the Great’s centralizing policies.
  • 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_69ca82f749388190bffbea6dfb509016 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb810e16b081908e2c25bfb9d590ed completed March 31, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc917acf881908aa76d38d7b62e0d completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:03 p.m.