Triple

T35876595
Position Surface form Disambiguated ID Type / Status
Subject Siegfried Rauch E1037380 entity
Predicate spouse P13 FINISHED
Object Karin Rauch
Karin Rauch is known as the wife of the late German actor Siegfried Rauch, who was famous for his roles in film and television.
E2163828 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: Karin Rauch | Statement: [Siegfried Rauch, spouse, Karin Rauch]
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: Karin Rauch
Triple: [Siegfried Rauch, spouse, Karin Rauch]
Generated description
Karin Rauch is known as the wife of the late German actor Siegfried Rauch, who was famous for his roles in film and television.

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_69f76e1e701c8190a4990d4978ce4fe6 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a9cf898c8190a44abebae80aa70c completed May 3, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38b6ed37388190bbd6b8ed80a63f9b completed June 22, 2026, 4:15 a.m.
NEDg Description generation batch_6a38b7d8c5fc8190a7cce91a93d1b905 completed June 22, 2026, 4:19 a.m.
NED2 Entity disambiguation (via description) batch_6a38b86a90b48190810a306e1cf50744 completed June 22, 2026, 4:22 a.m.
Created at: May 3, 2026, 4:06 p.m.