Triple

T35825360
Position Surface form Disambiguated ID Type / Status
Subject Nicholas II of Opava E1035626 entity
Predicate child P120 FINISHED
Object John I, Duke of Opava-Racibórz
John I, Duke of Opava-Racibórz was a 14th-century Silesian nobleman from the Přemyslid dynasty who ruled parts of the Opava and Racibórz territories.
E2174226 NE FINISHED

How this triple was built (2 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: John I, Duke of Opava-Racibórz | Statement: [Nicholas II of Opava, child, John I, Duke of Opava-Racibórz]
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: John I, Duke of Opava-Racibórz
Triple: [Nicholas II of Opava, child, John I, Duke of Opava-Racibórz]
Generated description
John I, Duke of Opava-Racibórz was a 14th-century Silesian nobleman from the Přemyslid dynasty who ruled parts of the Opava and Racibórz territories.

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_69f76e185ffc8190880b3cdf51decd38 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a902f7a481909819b583bccd4c8f completed May 3, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3933f8332081908b743f0713d7ba00 completed June 22, 2026, 1:09 p.m.
NEDg Description generation batch_6a39357be9248190ac0dc9a49cf9bc05 completed June 22, 2026, 1:15 p.m.
NED2 Entity disambiguation (via description) batch_6a393617dfbc8190a9098be4065253b7 completed June 22, 2026, 1:18 p.m.
Created at: May 3, 2026, 4:06 p.m.