Triple

T571552
Position Surface form Disambiguated ID Type / Status
Subject Charles E13673 entity
Predicate hasVariant P455 FINISHED
Object Karel
Karel is a given name, commonly used in Central and Eastern Europe, that corresponds to the English name Charles.
E71855 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: Karel | Statement: [Charles, hasVariant, Karel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karel
Context triple: [Charles, hasVariant, Karel]
  • A. Karl
    Karl is the given first name of Charles Proteus Steinmetz, the renowned German-American mathematician and electrical engineer who revolutionized the understanding of alternating current systems.
  • B. Karl
    Karl is the given name of German Field Marshal Gerd von Rundstedt, a prominent military leader during World War II.
  • C. Karol
    Karol is the given name of Pope John Paul II, the Polish-born head of the Catholic Church from 1978 to 2005.
  • D. Emil
    Emil is the given name of Carl Gustaf Emil Mannerheim, the renowned Finnish military leader and statesman who served as President of Finland.
  • E. Jozef
    Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
  • 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: Karel
Triple: [Charles, hasVariant, Karel]
Generated description
Karel is a given name, commonly used in Central and Eastern Europe, that corresponds to the English name Charles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Karel
Target entity description: Karel is a given name, commonly used in Central and Eastern Europe, that corresponds to the English name Charles.
  • A. Karl
    Karl is the given first name of Charles Proteus Steinmetz, the renowned German-American mathematician and electrical engineer who revolutionized the understanding of alternating current systems.
  • B. Karl
    Karl is the given name of German Field Marshal Gerd von Rundstedt, a prominent military leader during World War II.
  • C. Karol
    Karol is the given name of Pope John Paul II, the Polish-born head of the Catholic Church from 1978 to 2005.
  • D. Emil
    Emil is the given name of Carl Gustaf Emil Mannerheim, the renowned Finnish military leader and statesman who served as President of Finland.
  • E. Jozef
    Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b483ac08190b3be152a7cf42011 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ff4c3df48190a886a8d3c633d417 completed March 2, 2026, 3:09 a.m.
NEDg Description generation batch_69a4ffcad6e08190938018ade5bc5d67 completed March 2, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_69a5001de9c481909d43c001028c922c completed March 2, 2026, 3:12 a.m.
Created at: March 1, 2026, 7:33 p.m.