Triple

T25837481
Position Surface form Disambiguated ID Type / Status
Subject Invalids' Cemetery E650841 entity
Predicate containsGraveOf P3802 FINISHED
Object Johann Georg Emil von Brause
Johann Georg Emil von Brause was a Prussian general of the 19th century who served in the Napoleonic Wars and later held high-ranking commands in the Prussian Army.
E1880655 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: Johann Georg Emil von Brause | Statement: [Invalids' Cemetery, containsGraveOf, Johann Georg Emil von Brause]
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: Johann Georg Emil von Brause
Triple: [Invalids' Cemetery, containsGraveOf, Johann Georg Emil von Brause]
Generated description
Johann Georg Emil von Brause was a Prussian general of the 19th century who served in the Napoleonic Wars and later held high-ranking commands in the Prussian Army.

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_69e7ab38086081908f3a8e7e0c6efd83 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f601f6371081908534e009e4e1cc8f completed May 2, 2026, 1:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa4387b48190827f5e9c3557c8a7 completed June 8, 2026, 11:40 a.m.
NEDg Description generation batch_6a26ae71575081908f792ba4e0bce3f2 completed June 8, 2026, 11:58 a.m.
NED2 Entity disambiguation (via description) batch_6a26b2549840819082678037e8c97eb2 completed June 8, 2026, 12:15 p.m.
Created at: April 22, 2026, 7:47 a.m.