Triple

T718712
Position Surface form Disambiguated ID Type / Status
Subject Claudia E14367 entity
Predicate hasVariant P455 FINISHED
Object Klaudija
Klaudija is a feminine given name, commonly used in Slavic countries, that corresponds to the name Claudia.
E106191 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: Klaudija | Statement: [Claudia, hasVariant, Klaudija]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klaudija
Context triple: [Claudia, hasVariant, Klaudija]
  • A. Klara Dan
    Klara Dan was a Hungarian-American mathematician and computer programmer known for her pioneering work on early digital computers alongside her husband, John von Neumann.
  • B. Tanja Stomporowski
    Tanja Stomporowski is a German local politician who serves as the mayor of the town of Quakenbrück in Lower Saxony.
  • C. Johanna
    Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • 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: Klaudija
Triple: [Claudia, hasVariant, Klaudija]
Generated description
Klaudija is a feminine given name, commonly used in Slavic countries, that corresponds to the name Claudia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Klaudija
Target entity description: Klaudija is a feminine given name, commonly used in Slavic countries, that corresponds to the name Claudia.
  • A. Klara Dan
    Klara Dan was a Hungarian-American mathematician and computer programmer known for her pioneering work on early digital computers alongside her husband, John von Neumann.
  • B. Tanja Stomporowski
    Tanja Stomporowski is a German local politician who serves as the mayor of the town of Quakenbrück in Lower Saxony.
  • C. Johanna
    Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a58d4c3c8190ad4527d14bca5e6e completed March 1, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c70997d081908a10e1aa4e936d32 completed March 4, 2026, 5:45 a.m.
NEDg Description generation batch_69a7c78161608190a9f5556639f9d97d completed March 4, 2026, 5:47 a.m.
NED2 Entity disambiguation (via description) batch_69a7c7e336c8819082bb3523c84fde4e completed March 4, 2026, 5:49 a.m.
Created at: March 1, 2026, 7:37 p.m.