Triple

T10393899
Position Surface form Disambiguated ID Type / Status
Subject Göran E244957 entity
Predicate hasVariant P455 FINISHED
Object Goran
Goran is a masculine given name commonly used in various Slavic countries.
E859330 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: Goran | Statement: [Göran, hasVariant, Goran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Goran
Context triple: [Göran, hasVariant, Goran]
  • A. Vlatko
    Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
  • B. Danijel
    Danijel is the central male protagonist in the war drama film "In the Land of Blood and Honey," which explores a complex relationship set against the backdrop of the Bosnian War.
  • C. Ilija
    Ilija is a masculine given name of Slavic origin, commonly used in countries such as Bulgaria, Serbia, and North Macedonia.
  • D. Saša
    Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
  • E. Marko Ramius
    Marko Ramius is a highly skilled Soviet submarine captain who masterminds a risky defection to the West in Tom Clancy’s techno-thriller "The Hunt for Red October."
  • 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: Goran
Triple: [Göran, hasVariant, Goran]
Generated description
Goran is a masculine given name commonly used in various Slavic countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Goran
Target entity description: Goran is a masculine given name commonly used in various Slavic countries.
  • A. Vlatko
    Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
  • B. Danijel
    Danijel is the central male protagonist in the war drama film "In the Land of Blood and Honey," which explores a complex relationship set against the backdrop of the Bosnian War.
  • C. Ilija
    Ilija is a masculine given name of Slavic origin, commonly used in countries such as Bulgaria, Serbia, and North Macedonia.
  • D. Saša
    Saša is a given name commonly used in Slavic countries, often as a diminutive of Aleksandar or Aleksandra.
  • E. Marko Ramius
    Marko Ramius is a highly skilled Soviet submarine captain who masterminds a risky defection to the West in Tom Clancy’s techno-thriller "The Hunt for Red October."
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b795fc8190aa50ce3c7360ff83 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d795c8271c81908a6b67822050c06d completed April 9, 2026, 12:04 p.m.
NEDg Description generation batch_69d7975191ac8190b32eb6cc1f5c88aa completed April 9, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d798655c7c8190a5da5ef976102285 completed April 9, 2026, 12:15 p.m.
Created at: April 6, 2026, 12:06 p.m.