Triple

T34952044
Position Surface form Disambiguated ID Type / Status
Subject Jan Lucemburský E1008025 entity
Predicate předchůdceNaČeskémTrůně P14266 FINISHED
Object Jindřich Korutanský
Jindřich Korutanský byl rakouský vévoda z rodu Habsburků, který se stal dvakrát českým králem v období mocenských zápasů o český trůn na počátku 14. století.
 E2271823 NE FINISHED

How this triple was built (3 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: Jindřich Korutanský | Statement: [Jan Lucemburský, předchůdceNaČeskémTrůně, Jindřich Korutanský]
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: Jindřich Korutanský
Triple: [Jan Lucemburský, předchůdceNaČeskémTrůně, Jindřich Korutanský]
Generated description
Jindřich Korutanský byl rakouský vévoda z rodu Habsburků, který se stal dvakrát českým králem v období mocenských zápasů o český trůn na počátku 14. století.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: předchůdceNaČeskémTrůně
Context triple: [Jan Lucemburský, předchůdceNaČeskémTrůně, Jindřich Korutanský]
  • A. predecessorAsKingOfBohemia chosen
    Indicates that one entity was the immediately preceding holder of the kingship of Bohemia relative to another entity.
  • B. successorAsKingOfBohemia
    Indicates that one person became the next king of Bohemia after another person.
  • C. predecessorAsDukeOfAustria
    Indicates that one entity previously held the title of Duke of Austria immediately before another entity, establishing a direct succession relationship between them.
  • D. predecessorAsKingOfPoland
    Indicates that one person previously held the position of King of Poland immediately before another person.
  • E. predecessorAsDukeOfSaxony
    Indicates that one entity previously held the title of Duke of Saxony immediately before another entity.
  • F. None of above.

Provenance (6 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_69f76dc5d4308190b77553ee07b1ede6 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f782cea4c881908ada116c80eafa15 completed May 3, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41cc874ae88190bd163e4bcfe569f7 completed June 29, 2026, 1:38 a.m.
NEDg Description generation batch_6a41cdab97bc8190a6fef8d57f05a86e completed June 29, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_6a41ce4cee4481909d34941327630fb7 completed June 29, 2026, 1:45 a.m.
PD Predicate disambiguation batch_69f781020cc4819088c40cb8589504e4 completed May 3, 2026, 5:08 p.m.
Created at: May 3, 2026, 4 p.m.