Triple

T12311898
Position Surface form Disambiguated ID Type / Status
Subject Marie Jana Körbelová E293498 entity
Predicate givenName P17 FINISHED
Object Jana
Jana is a feminine given name commonly used in various European countries, often as a form of Johanna or Jane.
 E973244 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: Jana | Statement: [Marie Jana Körbelová, givenName, Jana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jana
Context triple: [Marie Jana Körbelová, givenName, Jana]
  • A. Zhanna
    Zhanna is a feminine given name commonly used in Russian and other Slavic cultures, equivalent to Jeanne or Joanna.
  • B. Jula
    Jula is a major Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
  • C. Yulia
    Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
  • D. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • E. Katja
    Katja is a diminutive or short form of the given name Katarina, commonly used in various Slavic and European 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: Jana
Triple: [Marie Jana Körbelová, givenName, Jana]
Generated description
Jana is a feminine given name commonly used in various European countries, often as a form of Johanna or Jane.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jana
Target entity description: Jana is a feminine given name commonly used in various European countries, often as a form of Johanna or Jane.
  • A. Zhanna
    Zhanna is a feminine given name commonly used in Russian and other Slavic cultures, equivalent to Jeanne or Joanna.
  • B. Jula
    Jula is a major Mande language widely used as a trade and lingua franca in parts of West Africa, particularly in Burkina Faso, Côte d’Ivoire, and Mali.
  • C. Yulia
    Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
  • D. Nadya
    Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
  • E. Katja
    Katja is a diminutive or short form of the given name Katarina, commonly used in various Slavic and European 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f02c0508190b10c0627cdaaba76 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e84fa708190854afc6afd425fd7 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f61f5d746c8190b5b0edfc4832bc6c completed May 2, 2026, 3:59 p.m.
NED2 Entity disambiguation (via description) batch_69f62041f2408190ad320fec5283abdd completed May 2, 2026, 4:03 p.m.
Created at: April 8, 2026, 9:53 p.m.