Triple

T10951074
Position Surface form Disambiguated ID Type / Status
Subject Branko Zebec E258726 entity
Predicate givenName P17 FINISHED
Object Branko
Branko is a masculine given name commonly used in Slavic countries, particularly in the Balkans.
 E896604 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: Branko | Statement: [Branko Zebec, givenName, Branko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Branko
Context triple: [Branko Zebec, givenName, Branko]
  • A. Vlatko
    Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
  • B. Duško
    Duško is the given name of Duško Tadić, a Bosnian Serb who became known as the first person tried by the International Criminal Tribunal for the former Yugoslavia for war crimes committed during the Bosnian War.
  • C. Saša
    Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
  • D. Radomir
    Radomir is a town in western Bulgaria known for its location in the Pernik Province and its proximity to the Struma River and the capital, Sofia.
  • E. Željko
    Željko is a masculine given name of South Slavic origin, commonly used in countries such as Croatia and Slovenia.
  • 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: Branko
Triple: [Branko Zebec, givenName, Branko]
Generated description
Branko is a masculine given name commonly used in Slavic countries, particularly in the Balkans.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Branko
Target entity description: Branko is a masculine given name commonly used in Slavic countries, particularly in the Balkans.
  • A. Vlatko
    Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
  • B. Duško
    Duško is the given name of Duško Tadić, a Bosnian Serb who became known as the first person tried by the International Criminal Tribunal for the former Yugoslavia for war crimes committed during the Bosnian War.
  • C. Saša
    Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
  • D. Radomir
    Radomir is a town in western Bulgaria known for its location in the Pernik Province and its proximity to the Struma River and the capital, Sofia.
  • E. Željko
    Željko is a masculine given name of South Slavic origin, commonly used in countries such as Croatia and Slovenia.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770fc156c8190826e124c13ce7242 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d733f7d88190b45df5c155ff5a46 completed April 18, 2026, 12:58 a.m.
NEDg Description generation batch_69e2ff1ddd2c8190b31f5007f7492a4e completed April 18, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69e3260494bc81909e3dd4829697fb72 completed April 18, 2026, 6:34 a.m.
Created at: April 8, 2026, 9:23 p.m.