Triple

T13871067
Position Surface form Disambiguated ID Type / Status
Subject My Cousin Vinny E333449 entity
Predicate mainCharacter P1183 FINISHED
Object Mona Lisa Vito
Mona Lisa Vito is a sharp-witted, knowledgeable auto mechanic and the fiancée of novice lawyer Vinny Gambini in the comedy film "My Cousin Vinny."
E1065412 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: Mona Lisa Vito | Statement: [My Cousin Vinny, mainCharacter, Mona Lisa Vito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mona Lisa Vito
Context triple: [My Cousin Vinny, mainCharacter, Mona Lisa Vito]
  • A. Lorenzo
    Lorenzo is a small town located in Crosby County in the U.S. state of Texas.
  • B. Lorenzo
    Lorenzo is a masculine given name of Italian origin, historically borne by notable figures such as the Renaissance humanist Lorenzo Valla.
  • C. Vito
    Vito is a masculine given name of Italian origin, famously borne by mob boss Vito Genovese and the fictional character Vito Corleone.
  • D. Leonardo Vetra
    Leonardo Vetra is a fictional CERN physicist and priest in Dan Brown's novel "Angels & Demons," known for his groundbreaking antimatter research and as the adoptive father of Vittoria Vetra.
  • E. Silvio Dante
    Silvio Dante is a fictional mobster and consigliere in the television series "The Sopranos," known for his loyalty, sharp suits, and deadpan demeanor.
  • 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: Mona Lisa Vito
Triple: [My Cousin Vinny, mainCharacter, Mona Lisa Vito]
Generated description
Mona Lisa Vito is a sharp-witted, knowledgeable auto mechanic and the fiancée of novice lawyer Vinny Gambini in the comedy film "My Cousin Vinny."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mona Lisa Vito
Target entity description: Mona Lisa Vito is a sharp-witted, knowledgeable auto mechanic and the fiancée of novice lawyer Vinny Gambini in the comedy film "My Cousin Vinny."
  • A. Lorenzo
    Lorenzo is a small town located in Crosby County in the U.S. state of Texas.
  • B. Lorenzo
    Lorenzo is a masculine given name of Italian origin, historically borne by notable figures such as the Renaissance humanist Lorenzo Valla.
  • C. Vito
    Vito is a masculine given name of Italian origin, famously borne by mob boss Vito Genovese and the fictional character Vito Corleone.
  • D. Leonardo Vetra
    Leonardo Vetra is a fictional CERN physicist and priest in Dan Brown's novel "Angels & Demons," known for his groundbreaking antimatter research and as the adoptive father of Vittoria Vetra.
  • E. Silvio Dante
    Silvio Dante is a fictional mobster and consigliere in the television series "The Sopranos," known for his loyalty, sharp suits, and deadpan demeanor.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c638248190bbe5d19f7b88d0f9 completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c107c20c81909dff0ca4a59fcc55 completed May 3, 2026, 9:41 p.m.
NEDg Description generation batch_69f7c20da9448190b3167b091bd39b94 completed May 3, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_69f7c2cc63148190b9ca2828abe54286 completed May 3, 2026, 9:49 p.m.
Created at: April 9, 2026, 10:14 p.m.