Triple

T6712763
Position Surface form Disambiguated ID Type / Status
Subject Nadezhda E153186 entity
Predicate relatedName P3889 FINISHED
Object Nadya
Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
 E616360 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: Nadya | Statement: [Nadezhda, relatedName, Nadya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nadya
Context triple: [Nadezhda, relatedName, Nadya]
  • A. Natalia
    Natalia was a short-lived Boer republic established in the 1830s in what is now KwaZulu-Natal, South Africa.
  • B. Natalya
    Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
  • C. Yulia
    Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
  • D. Katya
    Katya is a diminutive and affectionate form of the given name Catherine, commonly used in Slavic and other European cultures.
  • E. Yelena
    Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
  • 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: Nadya
Triple: [Nadezhda, relatedName, Nadya]
Generated description
Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nadya
Target entity description: Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • A. Natalia
    Natalia was a short-lived Boer republic established in the 1830s in what is now KwaZulu-Natal, South Africa.
  • B. Natalya
    Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
  • C. Yulia
    Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
  • D. Katya
    Katya is a diminutive and affectionate form of the given name Catherine, commonly used in Slavic and other European cultures.
  • E. Yelena
    Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d121a92c8190a03f384a8aba84da completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70af8a8bc81908a04683dbf3d7793 completed March 27, 2026, 10:55 p.m.
NEDg Description generation batch_69c70ba06a5c81909b65b52d21d37104 completed March 27, 2026, 10:58 p.m.
NED2 Entity disambiguation (via description) batch_69c70c755054819087d0db6f94d69eae completed March 27, 2026, 11:02 p.m.
Created at: March 27, 2026, 2:07 p.m.