Triple

T10920193
Position Surface form Disambiguated ID Type / Status
Subject Black Widow program E257926 entity
Predicate notableTrainee P3529 FINISHED
Object Anya Derevkova
Anya Derevkova is a Marvel Comics character trained as an elite assassin through the Soviet Black Widow program.
 E928158 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: Anya Derevkova | Statement: [Black Widow program, notableTrainee, Anya Derevkova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anya Derevkova
Context triple: [Black Widow program, notableTrainee, Anya Derevkova]
  • A. Alexandra Velyaminova
    Alexandra Velyaminova was a Russian noblewoman of the 14th century, best known as the mother of Grand Prince Dmitry Donskoy of Moscow.
  • B. Daria Grinkova
    Daria Grinkova is the daughter of Russian Olympic champion figure skaters Ekaterina Gordeeva and the late Sergei Grinkov.
  • C. Tania Fedorova
    Tania Fedorova is a fictional character known as "The Mysterious Lady," typically portrayed as an enigmatic and alluring woman whose hidden motives drive much of the story’s intrigue.
  • D. Tatyana Dyachenko
    Tatyana Dyachenko is a Russian political figure who served as an influential adviser and image consultant to her father, President Boris Yeltsin, during the 1990s.
  • E. Nina Aleshina
    Nina Aleshina was a Soviet architect known for designing Moscow Metro stations, including Kakhovskaya.
  • 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: Anya Derevkova
Triple: [Black Widow program, notableTrainee, Anya Derevkova]
Generated description
Anya Derevkova is a Marvel Comics character trained as an elite assassin through the Soviet Black Widow program.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anya Derevkova
Target entity description: Anya Derevkova is a Marvel Comics character trained as an elite assassin through the Soviet Black Widow program.
  • A. Alexandra Velyaminova
    Alexandra Velyaminova was a Russian noblewoman of the 14th century, best known as the mother of Grand Prince Dmitry Donskoy of Moscow.
  • B. Daria Grinkova
    Daria Grinkova is the daughter of Russian Olympic champion figure skaters Ekaterina Gordeeva and the late Sergei Grinkov.
  • C. Tania Fedorova
    Tania Fedorova is a fictional character known as "The Mysterious Lady," typically portrayed as an enigmatic and alluring woman whose hidden motives drive much of the story’s intrigue.
  • D. Tatyana Dyachenko
    Tatyana Dyachenko is a Russian political figure who served as an influential adviser and image consultant to her father, President Boris Yeltsin, during the 1990s.
  • E. Nina Aleshina
    Nina Aleshina was a Soviet architect known for designing Moscow Metro stations, including Kakhovskaya.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77081a0c48190b7aa4a482032d1ea completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6037fdf80819091fb2c8bf128582d completed April 20, 2026, 10:44 a.m.
NEDg Description generation batch_69e60d7fc1208190a3a7ff0229806714 completed April 20, 2026, 11:26 a.m.
NED2 Entity disambiguation (via description) batch_69e617fdaaa88190a1860fb00309596b completed April 20, 2026, 12:11 p.m.
Created at: April 8, 2026, 9:22 p.m.