Triple

T1927187
Position Surface form Disambiguated ID Type / Status
Subject Valentina Goryacheva E40858 entity
Predicate hasGivenName P17 FINISHED
Object Valentina
Valentina is a feminine given name of Latin origin, commonly used in various countries and associated with meanings related to strength and health.
 E216751 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: Valentina | Statement: [Valentina Goryacheva, hasGivenName, Valentina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Valentina
Context triple: [Valentina Goryacheva, hasGivenName, Valentina]
  • A. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • B. Valeria
    Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
  • C. Sonya
    Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
  • D. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • E. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • 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: Valentina
Triple: [Valentina Goryacheva, hasGivenName, Valentina]
Generated description
Valentina is a feminine given name of Latin origin, commonly used in various countries and associated with meanings related to strength and health.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Valentina
Target entity description: Valentina is a feminine given name of Latin origin, commonly used in various countries and associated with meanings related to strength and health.
  • A. Valeria
    Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
  • B. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • C. Sonya
    Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
  • D. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • E. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • 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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb263cdb8819084d0bda98a2a71e0 completed March 7, 2026, 5:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3eb5d2c8190b5afd16a822bf0e4 completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf4e94b5081909d4010612d81b917 completed March 8, 2026, 10:15 p.m.
NED2 Entity disambiguation (via description) batch_69adf60463d88190896cedb2b45a67ed completed March 8, 2026, 10:19 p.m.
Created at: March 4, 2026, 7:35 p.m.