Triple

T10500948
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of the Suebi E247669 entity
Predicate ruler P403 FINISHED
Object Miro
Miro was a 6th-century king of the Suebi in Gallaecia, known for his efforts to maintain the kingdom’s independence amid Visigothic expansion.
 E373892 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: Miro | Statement: [Kingdom of the Suebi, ruler, Miro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Miro
Context triple: [Kingdom of the Suebi, ruler, Miro]
  • A. Miro
    Miro is a common Finnish given name, often used for males and sometimes derived from longer names like Miroslav.
  • B. Mekiro
    Mekiro is one of the smaller islands that form part of the remote Gambier Islands archipelago in French Polynesia.
  • C. Mireo
    Mireo is a family of modern regional and commuter trains developed by Siemens Mobility, known for their energy efficiency, modular design, and suitability for short- to medium-distance rail services.
  • D. Miki
    Miki is a city in Japan located within Hyogo Prefecture, known for its traditional hardware industry and historical sites.
  • E. Mijas
    Mijas is a picturesque municipality in the province of Málaga in southern Spain, known for its whitewashed village, coastal resorts, and location along the Costa del Sol.
  • 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: Miro
Triple: [Kingdom of the Suebi, ruler, Miro]
Generated description
Miro was a 6th-century king of the Suebi in Gallaecia, known for his efforts to maintain the kingdom’s independence amid Visigothic expansion.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Miro
Target entity description: Miro was a 6th-century king of the Suebi in Gallaecia, known for his efforts to maintain the kingdom’s independence amid Visigothic expansion.
  • A. Miro chosen
    Miro is a common Finnish given name, often used for males and sometimes derived from longer names like Miroslav.
  • B. Mekiro
    Mekiro is one of the smaller islands that form part of the remote Gambier Islands archipelago in French Polynesia.
  • C. Mireo
    Mireo is a family of modern regional and commuter trains developed by Siemens Mobility, known for their energy efficiency, modular design, and suitability for short- to medium-distance rail services.
  • D. Miki
    Miki is a city in Japan located within Hyogo Prefecture, known for its traditional hardware industry and historical sites.
  • E. Mijas
    Mijas is a picturesque municipality in the province of Málaga in southern Spain, known for its whitewashed village, coastal resorts, and location along the Costa del Sol.
  • F. None of above.

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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5099b797c8190a94803fa94eb6981 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dccec72481909bcfb6a9c5df7ba9 completed April 10, 2026, 11:19 a.m.
NEDg Description generation batch_69d8e8c9d5cc8190a425ed834855bbcd completed April 10, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d901fecee88190999e88ca2e56a516 completed April 10, 2026, 1:58 p.m.
Created at: April 6, 2026, 12:25 p.m.