Triple

T22209042
Position Surface form Disambiguated ID Type / Status
Subject Symphony No. 9 in D minor E548891 entity
Predicate premiereConductor P4736 FINISHED
Object Ferdinand Löwe
Ferdinand Löwe was an Austrian conductor and music educator best known for his close association with Anton Bruckner’s works and for shaping the early performance tradition of Bruckner’s symphonies.
E1804228 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: Ferdinand Löwe | Statement: [Symphony No. 9 in D minor, premiereConductor, Ferdinand Löwe]
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: Ferdinand Löwe
Triple: [Symphony No. 9 in D minor, premiereConductor, Ferdinand Löwe]
Generated description
Ferdinand Löwe was an Austrian conductor and music educator best known for his close association with Anton Bruckner’s works and for shaping the early performance tradition of Bruckner’s symphonies.

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_69e11e3f7e04819089806d81d5ac431e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b29eb808190ab8abaa1e0e354fa completed April 28, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15d76a3c6c819094455069fdee5547 completed May 26, 2026, 5:24 p.m.
NEDg Description generation batch_6a15d82ac0fc819082a575f3f11f25da completed May 26, 2026, 5:28 p.m.
NED2 Entity disambiguation (via description) batch_6a15d8e229e88190aaf00c672b1bf5da completed May 26, 2026, 5:31 p.m.
Created at: April 16, 2026, 8:36 p.m.