Triple

T2577329
Position Surface form Disambiguated ID Type / Status
Subject Fidelio, Op. 72 E57006 entity
Predicate mainCharacter P1183 FINISHED
Object Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
 E280013 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: Marzelline | Statement: [Fidelio, Op. 72, mainCharacter, Marzelline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marzelline
Context triple: [Fidelio, Op. 72, mainCharacter, Marzelline]
  • A. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • B. Lizella
    Lizella is an unincorporated community in central Georgia, United States, located near the city of Macon.
  • C. Corinna
    Corinna was an ancient Greek lyric poet from Boeotia, renowned for her choral poetry composed in the Aeolic dialect.
  • D. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • E. Zella
    Zella is an activewear and athleisure clothing brand known for its performance-focused yet stylish designs, sold at Nordstrom.
  • 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: Marzelline
Triple: [Fidelio, Op. 72, mainCharacter, Marzelline]
Generated description
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marzelline
Target entity description: Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
  • A. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • B. Lizella
    Lizella is an unincorporated community in central Georgia, United States, located near the city of Macon.
  • C. Corinna
    Corinna was an ancient Greek lyric poet from Boeotia, renowned for her choral poetry composed in the Aeolic dialect.
  • D. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • E. Zella
    Zella is an activewear and athleisure clothing brand known for its performance-focused yet stylish designs, sold at Nordstrom.
  • 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_69ab4a4dca6481908c301f8e317396e7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3a73a508190bf12e889a5d4bbf3 completed March 7, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69af6576a0a8819080d9241801675b19 completed March 10, 2026, 12:27 a.m.
NEDg Description generation batch_69af669436208190901d1f34592c1a42 completed March 10, 2026, 12:32 a.m.
NED2 Entity disambiguation (via description) batch_69af6760cf7c8190bb681f573828049e completed March 10, 2026, 12:35 a.m.
Created at: March 6, 2026, 9:49 p.m.