Triple

T30108476
Position Surface form Disambiguated ID Type / Status
Subject Lieder by Johannes Brahms E765195 entity
Predicate includesWork P2011 FINISHED
Object Magelone-Romanzen, Op. 33
Magelone-Romanzen, Op. 33 is a song cycle by Johannes Brahms for voice and piano, based on Ludwig Tieck’s romantic tale “Die schöne Magelone.”
 E1899145 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: Magelone-Romanzen, Op. 33 | Statement: [Lieder by Johannes Brahms, includesWork, Magelone-Romanzen, Op. 33]
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: Magelone-Romanzen, Op. 33
Triple: [Lieder by Johannes Brahms, includesWork, Magelone-Romanzen, Op. 33]
Generated description
Magelone-Romanzen, Op. 33 is a song cycle by Johannes Brahms for voice and piano, based on Ludwig Tieck’s romantic tale “Die schöne Magelone.”

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_69f22475ad7c8190be7f9541044a0bbb completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67dbd1c648190b9dfee119e380a31 completed May 2, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27433526c48190917648ff3c24fc31 completed June 8, 2026, 10:33 p.m.
NEDg Description generation batch_6a274425ee608190bffe31a54f427e7b completed June 8, 2026, 10:37 p.m.
NED2 Entity disambiguation (via description) batch_6a2744eb21688190939820a2659d99c5 completed June 8, 2026, 10:40 p.m.
Created at: April 29, 2026, 7:10 p.m.