Triple

T10240556
Position Surface form Disambiguated ID Type / Status
Subject Arturo E243576 entity
Predicate hasCognate P2525 FINISHED
Object Artur (Catalan)
Artur (Catalan) is the Catalan form of the given name Arthur, commonly used in Catalan-speaking regions.
 E853449 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: Artur (Catalan) | Statement: [Arturo, hasCognate, Artur (Catalan)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Artur (Catalan)
Context triple: [Arturo, hasCognate, Artur (Catalan)]
  • A. Sergi
    Sergi is a masculine given name of Catalan origin, commonly used in Spain and other Catalan-speaking regions.
  • B. Noguès
    Noguès is a French surname borne by various notable individuals, including figures in politics, arts, and sports.
  • C. Raimón
    Raimón is a given name, commonly used in Spanish- and Catalan-speaking regions, that serves as a variant of the name Ramón.
  • D. Miquèl
    Miquèl is a given name, likely a regional or accented variant of the name Miquel used in certain Romance-language contexts.
  • E. Josep
    Josep "Pep" Guardiola is a highly successful Spanish football manager and former player, renowned for his innovative tactics and trophy-laden spells at clubs like FC Barcelona, Bayern Munich, and Manchester City.
  • 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: Artur (Catalan)
Triple: [Arturo, hasCognate, Artur (Catalan)]
Generated description
Artur (Catalan) is the Catalan form of the given name Arthur, commonly used in Catalan-speaking regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Artur (Catalan)
Target entity description: Artur (Catalan) is the Catalan form of the given name Arthur, commonly used in Catalan-speaking regions.
  • A. Sergi
    Sergi is a masculine given name of Catalan origin, commonly used in Spain and other Catalan-speaking regions.
  • B. Noguès
    Noguès is a French surname borne by various notable individuals, including figures in politics, arts, and sports.
  • C. Raimón
    Raimón is a given name, commonly used in Spanish- and Catalan-speaking regions, that serves as a variant of the name Ramón.
  • D. Miquèl
    Miquèl is a given name, likely a regional or accented variant of the name Miquel used in certain Romance-language contexts.
  • E. Josep
    Josep "Pep" Guardiola is a highly successful Spanish football manager and former player, renowned for his innovative tactics and trophy-laden spells at clubs like FC Barcelona, Bayern Munich, and Manchester City.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d21e27f08190b956d351a75c7c52 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f780c7808190993e7c37cb4d18a3 completed April 9, 2026, 12:49 a.m.
NEDg Description generation batch_69d6fa2f7a848190a9de5de4d0f3f110 completed April 9, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69d6fcbab3ec8190ade1c0223c22ad58 completed April 9, 2026, 1:11 a.m.
Created at: April 6, 2026, 11:24 a.m.