Triple

T10282593
Position Surface form Disambiguated ID Type / Status
Subject Til Schweiger E241140 entity
Predicate notableWork P4 FINISHED
Object Zweiohrküken
Zweiohrküken is a 2009 German romantic comedy film and sequel to Keinohrhasen, directed by and starring Til Schweiger.
E852530 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: Zweiohrküken | Statement: [Til Schweiger, notableWork, Zweiohrküken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zweiohrküken
Context triple: [Til Schweiger, notableWork, Zweiohrküken]
  • A. Fischeln
    Fischeln is a district of the German city of Krefeld in the state of North Rhine-Westphalia.
  • B. Schaufling
    Schaufling is a small municipality in the Bavarian district of Regen in southeastern Germany, known for its rural setting in the Bavarian Forest region.
  • C. Bierden
    Bierden is a district of the town of Achim in Lower Saxony, Germany.
  • D. Hinteri Egg
    Hinteri Egg is a mountain peak in Switzerland that forms the highest point of the canton of Basel-Landschaft.
  • E. Hahnen
    Hahnen is a prominent mountain peak in the Swiss Alps near the resort town of Engelberg, known for its striking rocky profile and alpine scenery.
  • 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: Zweiohrküken
Triple: [Til Schweiger, notableWork, Zweiohrküken]
Generated description
Zweiohrküken is a 2009 German romantic comedy film and sequel to Keinohrhasen, directed by and starring Til Schweiger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zweiohrküken
Target entity description: Zweiohrküken is a 2009 German romantic comedy film and sequel to Keinohrhasen, directed by and starring Til Schweiger.
  • A. Fischeln
    Fischeln is a district of the German city of Krefeld in the state of North Rhine-Westphalia.
  • B. Schaufling
    Schaufling is a small municipality in the Bavarian district of Regen in southeastern Germany, known for its rural setting in the Bavarian Forest region.
  • C. Bierden
    Bierden is a district of the town of Achim in Lower Saxony, Germany.
  • D. Hinteri Egg
    Hinteri Egg is a mountain peak in Switzerland that forms the highest point of the canton of Basel-Landschaft.
  • E. Hahnen
    Hahnen is a prominent mountain peak in the Swiss Alps near the resort town of Engelberg, known for its striking rocky profile and alpine scenery.
  • 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_69d6f83c3c488190b728783bc260b006 completed April 9, 2026, 12:52 a.m.
NEDg Description generation batch_69d6fcae243c819095a2e791716805bd completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd3495fc8190a093d2536cfbe58a completed April 9, 2026, 1:13 a.m.
Created at: April 6, 2026, 11:39 a.m.