Triple

T6362768
Position Surface form Disambiguated ID Type / Status
Subject Auf Wiedersehen, Pet E143149 entity
Predicate mainCharacter P1183 FINISHED
Object Moxey
Moxey is a shy, hapless bricklayer and one of the central members of the group of British migrant workers in the comedy-drama series "Auf Wiedersehen, Pet."
 E588114 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: Moxey | Statement: [Auf Wiedersehen, Pet, mainCharacter, Moxey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Moxey
Context triple: [Auf Wiedersehen, Pet, mainCharacter, Moxey]
  • A. Hassler
    Hassler Whitney was an influential American mathematician known for his foundational work in differential topology and manifold theory.
  • B. Bonger
    Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
  • C. Ottis
    Ottis is a masculine given name most notably borne by former NFL running back Ottis Anderson.
  • D. Payette
    Payette is a French-Canadian surname most notably associated with Julie Payette, an engineer, astronaut, and former Governor General of Canada.
  • E. Gurney
    Gurney is an English surname historically associated with several notable families, including Quaker bankers, philanthropists, and public figures.
  • 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: Moxey
Triple: [Auf Wiedersehen, Pet, mainCharacter, Moxey]
Generated description
Moxey is a shy, hapless bricklayer and one of the central members of the group of British migrant workers in the comedy-drama series "Auf Wiedersehen, Pet."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Moxey
Target entity description: Moxey is a shy, hapless bricklayer and one of the central members of the group of British migrant workers in the comedy-drama series "Auf Wiedersehen, Pet."
  • A. Hassler
    Hassler Whitney was an influential American mathematician known for his foundational work in differential topology and manifold theory.
  • B. Bonger
    Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
  • C. Ottis
    Ottis is a masculine given name most notably borne by former NFL running back Ottis Anderson.
  • D. Payette
    Payette is a French-Canadian surname most notably associated with Julie Payette, an engineer, astronaut, and former Governor General of Canada.
  • E. Gurney
    Gurney is an English surname historically associated with several notable families, including Quaker bankers, philanthropists, and public figures.
  • 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_69c008d7a9c4819098d647ec47776917 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0680c02b481908618317566e31a5c completed March 22, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d73a6ac8190a02602c3506e4226 completed March 27, 2026, 7:10 a.m.
NEDg Description generation batch_69c62f2abb7481909a8d6b6a3b07db37 completed March 27, 2026, 7:18 a.m.
NED2 Entity disambiguation (via description) batch_69c62fcd18a0819089fa5f5912f432aa completed March 27, 2026, 7:20 a.m.
Created at: March 22, 2026, 4:32 p.m.