Triple

T24865341
Position Surface form Disambiguated ID Type / Status
Subject Die Lorelei E622262 entity
Predicate musicBy P1952 FINISHED
Object Friedrich Silcher
Friedrich Silcher was a 19th-century German composer and music educator best known for his influential arrangements of folk songs and art songs that became staples of German musical culture.
E1656119 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: Friedrich Silcher | Statement: [Die Lorelei, musicBy, Friedrich Silcher]
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: Friedrich Silcher
Triple: [Die Lorelei, musicBy, Friedrich Silcher]
Generated description
Friedrich Silcher was a 19th-century German composer and music educator best known for his influential arrangements of folk songs and art songs that became staples of German musical culture.

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_69e2fac350d08190b3affde1b451a8c5 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f42301aeb881908aaa79cc99cc7dec completed May 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10331b0dc08190b5489559c59be6b0 completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a10341e764c819083c10e4d151da1c6 completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1034c45fb88190865f904fd8e766b3 completed May 22, 2026, 10:49 a.m.
Created at: April 18, 2026, 5:22 a.m.