Triple

T16374752
Position Surface form Disambiguated ID Type / Status
Subject ECM Records E397651 entity
Predicate associatedWithArtist P5936 FINISHED
Object Eberhard Weber
Eberhard Weber is a German double bassist and composer known for his distinctive lyrical style and influential jazz and fusion recordings, particularly on the ECM label.
E1697370 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: Eberhard Weber | Statement: [ECM Records, associatedWithArtist, Eberhard Weber]
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: Eberhard Weber
Triple: [ECM Records, associatedWithArtist, Eberhard Weber]
Generated description
Eberhard Weber is a German double bassist and composer known for his distinctive lyrical style and influential jazz and fusion recordings, particularly on the ECM label.

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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319d6942081909616a2c6efee9967 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9cc70808190b72a2d2bf7d14568 completed May 22, 2026, 10:33 p.m.
NEDg Description generation batch_6a10ddc8e4188190959ea1e7d360aba5 completed May 22, 2026, 10:50 p.m.
NED2 Entity disambiguation (via description) batch_6a10de259fd4819087f0f5707196792d completed May 22, 2026, 10:52 p.m.
Created at: April 10, 2026, 5:08 a.m.