Triple

T34389435
Position Surface form Disambiguated ID Type / Status
Subject Magdalene Sibylle of Saxe-Weissenfels E882652 entity
Predicate child P120 FINISHED
Object Albrecht, Duke of Saxe-Coburg
Albrecht, Duke of Saxe-Coburg, was a German nobleman of the Ernestine Wettin line who ruled the small duchy of Saxe-Coburg in the early 17th century.
E2098228 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: Albrecht, Duke of Saxe-Coburg | Statement: [Magdalene Sibylle of Saxe-Weissenfels, child, Albrecht, Duke of Saxe-Coburg]
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: Albrecht, Duke of Saxe-Coburg
Triple: [Magdalene Sibylle of Saxe-Weissenfels, child, Albrecht, Duke of Saxe-Coburg]
Generated description
Albrecht, Duke of Saxe-Coburg, was a German nobleman of the Ernestine Wettin line who ruled the small duchy of Saxe-Coburg in the early 17th century.

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_69f349c0219881909393bbbc1edc8161 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7187a0f088190882f80298bfaa9d6 completed May 3, 2026, 9:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37211fbc508190a0daf2aa5b63e3ba completed June 20, 2026, 11:24 p.m.
NEDg Description generation batch_6a3721d614908190a25d92255fe1b393 completed June 20, 2026, 11:27 p.m.
NED2 Entity disambiguation (via description) batch_6a372258e0948190807baa91b3465ef8 completed June 20, 2026, 11:29 p.m.
Created at: May 1, 2026, 1:59 a.m.