Triple

T2859894
Position Surface form Disambiguated ID Type / Status
Subject Lydia Ivanova E63293 entity
Predicate familyName P18 FINISHED
Object Ivanova
Ivanova is a common Slavic surname, particularly prevalent in Russia and other Eastern European countries, typically indicating female lineage from someone named Ivan.
 E306489 NE FINISHED

How this triple was built (4 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: Ivanova | Statement: [Lydia Ivanova, familyName, Ivanova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ivanova
Context triple: [Lydia Ivanova, familyName, Ivanova]
  • A. Zhdanova
    Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
  • B. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • C. Khodchenkova
    Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
  • D. Ivanovich
    Ivanovich is a common Russian patronymic meaning “son of Ivan,” frequently used as a middle name in Russian full names.
  • E. Katerina Tikhonova
    Katerina Tikhonova is a Russian academic and business executive widely reported to be one of Vladimir Putin’s daughters, known for her roles in scientific institutions and high-tech investment projects.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ivanova
Triple: [Lydia Ivanova, familyName, Ivanova]
Generated description
Ivanova is a common Slavic surname, particularly prevalent in Russia and other Eastern European countries, typically indicating female lineage from someone named Ivan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ivanova
Target entity description: Ivanova is a common Slavic surname, particularly prevalent in Russia and other Eastern European countries, typically indicating female lineage from someone named Ivan.
  • A. Zhdanova
    Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
  • B. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • C. Khodchenkova
    Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
  • D. Ivanovich
    Ivanovich is a common Russian patronymic meaning “son of Ivan,” frequently used as a middle name in Russian full names.
  • E. Katerina Tikhonova
    Katerina Tikhonova is a Russian academic and business executive widely reported to be one of Vladimir Putin’s daughters, known for her roles in scientific institutions and high-tech investment projects.
  • F. None of above. chosen

Provenance (5 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_69ab4c41e8c08190a9e8f5249cc12610 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf8aec3c8190a4168d8c916b5268 completed March 7, 2026, 8:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d972aa481908f6cb5f27706990c completed March 10, 2026, 1:33 p.m.
NEDg Description generation batch_69b021fbc2808190b415fd8af934cf73 completed March 10, 2026, 1:51 p.m.
NED2 Entity disambiguation (via description) batch_69b02656f8488190ab0d715d1634b6a7 completed March 10, 2026, 2:10 p.m.
Created at: March 6, 2026, 10:02 p.m.