Triple

T23082210
Position Surface form Disambiguated ID Type / Status
Subject Velimir Perasović E575505 entity
Predicate givenName P17 FINISHED
Object Velimir
Velimir is a Croatian former professional basketball player and coach known for his successful European club career and leadership of the Croatian national team.
 E1571921 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: Velimir | Statement: [Velimir Perasović, givenName, Velimir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Velimir
Context triple: [Velimir Perasović, givenName, Velimir]
  • A. Milutin
    Milutin is a masculine given name of Slavic origin, commonly used in Serbian and other South Slavic cultures.
  • B. 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.
  • C. Vlatko
    Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
  • D. Stjepan
    Stjepan is a Croatian masculine given name, equivalent to Stephen, commonly borne by notable figures in Croatian history and politics.
  • E. Pavle
    Pavle is a South Slavic male given name commonly used in countries such as Serbia, Croatia, and Montenegro, equivalent to Paul in English.
  • 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: Velimir
Triple: [Velimir Perasović, givenName, Velimir]
Generated description
Velimir is a Croatian former professional basketball player and coach known for his successful European club career and leadership of the Croatian national team.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Velimir
Target entity description: Velimir is a Croatian former professional basketball player and coach known for his successful European club career and leadership of the Croatian national team.
  • A. Milutin
    Milutin is a masculine given name of Slavic origin, commonly used in Serbian and other South Slavic cultures.
  • B. 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.
  • C. Vlatko
    Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
  • D. Stjepan
    Stjepan is a Croatian masculine given name, equivalent to Stephen, commonly borne by notable figures in Croatian history and politics.
  • E. Pavle
    Pavle is a South Slavic male given name commonly used in countries such as Serbia, Croatia, and Montenegro, equivalent to Paul in English.
  • 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_69e245be28d48190ad1348d5a73db37d completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18da239e48190ad041261c6b510a0 completed April 29, 2026, 4:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c23dca4c08190a9619956a45aa17a completed May 19, 2026, 8:48 a.m.
NEDg Description generation batch_6a0c271d8fc48190a818c73660218022 completed May 19, 2026, 9:02 a.m.
NED2 Entity disambiguation (via description) batch_6a0c2951a718819088c1c7d8435586ec completed May 19, 2026, 9:11 a.m.
Created at: April 17, 2026, 3:56 p.m.