Triple

T1089723
Position Surface form Disambiguated ID Type / Status
Subject Sophia Tolstaya E24133 entity
Predicate givenName P17 FINISHED
Object Sofya
Sofya is the Russian given name of Sophia Tolstaya, the wife and muse of novelist Leo Tolstoy.
 E141376 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: Sofya | Statement: [Sophia Tolstaya, givenName, Sofya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sofya
Context triple: [Sophia Tolstaya, givenName, Sofya]
  • A. Sofia
    Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
  • B. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • C. Tsaritsyn
    Tsaritsyn was the original name of the Russian city now known as Volgograd, a major industrial and historical center on the Volga River.
  • D. Moscow
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • E. Moscow
    Moscow is a fictional character from the Spanish television series "Money Heist" (La Casa de Papel), known as a kind-hearted, blue-collar miner and the father of Denver who participates in the Royal Mint heist.
  • 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: Sofya
Triple: [Sophia Tolstaya, givenName, Sofya]
Generated description
Sofya is the Russian given name of Sophia Tolstaya, the wife and muse of novelist Leo Tolstoy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sofya
Target entity description: Sofya is the Russian given name of Sophia Tolstaya, the wife and muse of novelist Leo Tolstoy.
  • A. Sofia
    Sofia is the capital and largest city of Bulgaria, known as a major cultural, economic, and historical center in the Balkans.
  • B. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • C. Tsaritsyn
    Tsaritsyn was the original name of the Russian city now known as Volgograd, a major industrial and historical center on the Volga River.
  • D. Moscow
    Moscow is a fictional character from the Spanish television series "Money Heist" (La Casa de Papel), known as a kind-hearted, blue-collar miner and the father of Denver who participates in the Royal Mint heist.
  • E. Moscow
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b97f216881909e9b8943ce2078e4 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac89fd91208190ac962ec7059f716b completed March 7, 2026, 8:26 p.m.
NEDg Description generation batch_69ac8becbbe48190a12b3814982c5c8f completed March 7, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69ac8c471754819096bcca9fea985a9f completed March 7, 2026, 8:36 p.m.
Created at: March 1, 2026, 7:42 p.m.