Triple

T37360255
Position Surface form Disambiguated ID Type / Status
Subject Jörg Widmann E927556 entity
Predicate hasSibling P363 FINISHED
Object Carolin Widmann
Carolin Widmann is a renowned German violinist celebrated for her interpretations of both contemporary and classical repertoire.
E2250560 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: Carolin Widmann | Statement: [Jörg Widmann, hasSibling, Carolin Widmann]
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: Carolin Widmann
Triple: [Jörg Widmann, hasSibling, Carolin Widmann]
Generated description
Carolin Widmann is a renowned German violinist celebrated for her interpretations of both contemporary and classical repertoire.

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_69f76eb701788190b40824bc4594d985 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5bc745448190b0f0224035a4ba6e completed May 6, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117d5076481908fa3dedf9eb39ae8 completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a41184a43e88190a7d559332bdd2b0b completed June 28, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_6a4126c2c2f08190b6c15693a083c594 completed June 28, 2026, 1:50 p.m.
Created at: May 3, 2026, 4:16 p.m.