Triple

T19150109
Position Surface form Disambiguated ID Type / Status
Subject Tatyana Larina E468781 entity
Predicate givenName P17 FINISHED
Object Tatyana 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: Tatyana | Statement: [Tatyana Larina, givenName, Tatyana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tatyana
Context triple: [Tatyana Larina, givenName, Tatyana]
  • A. Tatyana chosen
    Tatyana is a feminine given name of Slavic origin, particularly common in Russian-speaking countries.
  • B. Наташа
    Наташа — одна из главных героинь пьесы Максима Горького «На дне», олицетворяющая трагическую судьбу бедной и угнетённой женщины в мире социального дна.
  • C. Darya Saltykova
    Darya Saltykova was an 18th-century Russian noblewoman and notorious serial killer infamous for torturing and murdering numerous serfs on her estate.
  • D. Anastasia Markovna
    Anastasia Markovna was the wife of the 17th-century Russian Old Believer leader and writer Protopope Avvakum, remembered for her steadfast support during his religious persecution.
  • E. Alyonushka
    Alyonushka is a famous 1881 painting by Russian artist Viktor Vasnetsov depicting a melancholy peasant girl from Slavic folklore sitting by a forest pond.
  • 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e97c42348190875a2f5b5bc0b99e completed April 20, 2026, 8:53 a.m.
Created at: April 10, 2026, 12:06 p.m.