Triple

T11590379
Position Surface form Disambiguated ID Type / Status
Subject Così fan tutte E274863 entity
Predicate principalCharacter P9202 FINISHED
Object Don Alfonso
Don Alfonso is the cynical, manipulative philosopher in Mozart’s opera "Così fan tutte" who orchestrates a wager to test the fidelity of two young women.
E934171 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: Don Alfonso | Statement: [Così fan tutte, principalCharacter, Don Alfonso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Alfonso
Context triple: [Così fan tutte, principalCharacter, Don Alfonso]
  • A. Alfonso Santacana
    Alfonso Santacana was a film editor best known for his work on the 1964 science fiction horror film "The Last Man on Earth."
  • B. Alfrédo
    Alfrédo is a given name, likely a variant or cognate of "Alfred" or "Alfredo," used as a personal male first name in various languages.
  • C. Alvarito
    Alvarito is a Spanish diminutive form of the given name Álvaro, typically used as an affectionate nickname.
  • D. Elicio
    Elicio is a shepherd and one of the principal pastoral protagonists in Miguel de Cervantes’ early novel "La Galatea."
  • E. Don Benito
    Don Benito is a town in the province of Badajoz, in Spain’s Extremadura region, known for its agricultural economy and close association with the nearby town of Villanueva de la Serena.
  • 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: Don Alfonso
Triple: [Così fan tutte, principalCharacter, Don Alfonso]
Generated description
Don Alfonso is the cynical, manipulative philosopher in Mozart’s opera "Così fan tutte" who orchestrates a wager to test the fidelity of two young women.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Don Alfonso
Target entity description: Don Alfonso is the cynical, manipulative philosopher in Mozart’s opera "Così fan tutte" who orchestrates a wager to test the fidelity of two young women.
  • A. Alfonso Santacana
    Alfonso Santacana was a film editor best known for his work on the 1964 science fiction horror film "The Last Man on Earth."
  • B. Alfrédo
    Alfrédo is a given name, likely a variant or cognate of "Alfred" or "Alfredo," used as a personal male first name in various languages.
  • C. Alvarito
    Alvarito is a Spanish diminutive form of the given name Álvaro, typically used as an affectionate nickname.
  • D. Elicio
    Elicio is a shepherd and one of the principal pastoral protagonists in Miguel de Cervantes’ early novel "La Galatea."
  • E. Don Benito
    Don Benito is a town in the province of Badajoz, in Spain’s Extremadura region, known for its agricultural economy and close association with the nearby town of Villanueva de la Serena.
  • 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_69d6aae6b14c81908dc5a74bad7591f9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d894643ae48190837502b713f5b9c6 completed April 10, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69e714634b308190bdcb761f8b6712e7 completed April 21, 2026, 6:08 a.m.
NEDg Description generation batch_69e720fc0f38819083bd15169f2ce4bb completed April 21, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69e72353c19c8190b7a579e9af823872 completed April 21, 2026, 7:12 a.m.
Created at: April 8, 2026, 9:38 p.m.