Triple

T10282613
Position Surface form Disambiguated ID Type / Status
Subject Til Schweiger E241140 entity
Predicate hasChild P369 FINISHED
Object Emma Schweiger
Emma Schweiger is a German-American actress known for appearing in several of her father Til Schweiger’s films, including the popular comedy "Kokowääh."
E857479 NE FINISHED

How this triple was built (4 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: Emma Schweiger | Statement: [Til Schweiger, hasChild, Emma Schweiger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emma Schweiger
Context triple: [Til Schweiger, hasChild, Emma Schweiger]
  • A. Luna Schweiger
    Luna Schweiger is a German actress and model known for appearing in several films directed by her father, Til Schweiger, including "Keinohrhasen" and its sequels.
  • B. Lilli Schweiger
    Lilli Schweiger is a German actress and model, known for appearing in several films alongside her father, Til Schweiger.
  • C. Sabine Ganz
    Sabine Ganz is known as the spouse of the late Swiss actor Bruno Ganz, acclaimed for his roles in European cinema and theater.
  • D. Johanna Schall
    Johanna Schall is a German actress and theatre director, and the granddaughter of playwright Bertolt Brecht.
  • E. Annette Kurschus
    Annette Kurschus is a German Protestant theologian and bishop who has served as a leading figure in the Evangelical Church in Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Emma Schweiger
Triple: [Til Schweiger, hasChild, Emma Schweiger]
Generated description
Emma Schweiger is a German-American actress known for appearing in several of her father Til Schweiger’s films, including the popular comedy "Kokowääh."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Emma Schweiger
Target entity description: Emma Schweiger is a German-American actress known for appearing in several of her father Til Schweiger’s films, including the popular comedy "Kokowääh."
  • A. Luna Schweiger
    Luna Schweiger is a German actress and model known for appearing in several films directed by her father, Til Schweiger, including "Keinohrhasen" and its sequels.
  • B. Lilli Schweiger
    Lilli Schweiger is a German actress and model, known for appearing in several films alongside her father, Til Schweiger.
  • C. Sabine Ganz
    Sabine Ganz is known as the spouse of the late Swiss actor Bruno Ganz, acclaimed for his roles in European cinema and theater.
  • D. Johanna Schall
    Johanna Schall is a German actress and theatre director, and the granddaughter of playwright Bertolt Brecht.
  • E. Annette Kurschus
    Annette Kurschus is a German Protestant theologian and bishop who has served as a leading figure in the Evangelical Church in Germany.
  • F. None of above. chosen

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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2a22f9881908b220dbe1e80c101 completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d750097f1c8190a4b04e3758c89aae completed April 9, 2026, 7:06 a.m.
NEDg Description generation batch_69d7618b0f2481908149596dc86d4593 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77015ae688190870976309e2b912b completed April 9, 2026, 9:23 a.m.
Created at: April 6, 2026, 11:39 a.m.