Triple

T11137665
Position Surface form Disambiguated ID Type / Status
Subject Giovanna E263455 entity
Predicate shortForm P43 FINISHED
Object Vanna
Vanna is a given name, often used as a diminutive or variant of the name Giovanna.
 E907420 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: Vanna | Statement: [Giovanna, shortForm, Vanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vanna
Context triple: [Giovanna, shortForm, Vanna]
  • A. Vanessa
    Vanessa is the enigmatic, emotionally complex woman at the center of the film "By the Sea," whose inner turmoil drives the story’s exploration of marriage and personal grief.
  • B. Vanessa
    Vanessa is an English feminine given name that gained wider recognition through public figures such as Vanessa Trump.
  • C. Vanessa
    Vanessa is a fictional character associated with the setting of a beauty shop, likely depicted as someone involved in or frequenting the salon environment.
  • D. Vanita
    Vanita is a minor but pivotal character in Salman Rushdie’s novel "Midnight’s Children," known primarily as the biological mother of the protagonist Saleem Sinai.
  • E. Vonnie
    Vonnie is the given first name of Von Miller, the prominent American football linebacker and Super Bowl MVP.
  • 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: Vanna
Triple: [Giovanna, shortForm, Vanna]
Generated description
Vanna is a given name, often used as a diminutive or variant of the name Giovanna.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vanna
Target entity description: Vanna is a given name, often used as a diminutive or variant of the name Giovanna.
  • A. Vanessa
    Vanessa is an English feminine given name that gained wider recognition through public figures such as Vanessa Trump.
  • B. Vanessa
    Vanessa is the enigmatic, emotionally complex woman at the center of the film "By the Sea," whose inner turmoil drives the story’s exploration of marriage and personal grief.
  • C. Vanessa
    Vanessa is a fictional character associated with the setting of a beauty shop, likely depicted as someone involved in or frequenting the salon environment.
  • D. Vanita
    Vanita is a minor but pivotal character in Salman Rushdie’s novel "Midnight’s Children," known primarily as the biological mother of the protagonist Saleem Sinai.
  • E. Vonnie
    Vonnie is the given first name of Von Miller, the prominent American football linebacker and Super Bowl MVP.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e85f2ea48190bf1ff63af1d7d236 completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e442030b588190bc958030f30b648a completed April 19, 2026, 2:46 a.m.
NEDg Description generation batch_69e44c09dd5c8190bddf3dd109a639ba completed April 19, 2026, 3:29 a.m.
NED2 Entity disambiguation (via description) batch_69e451274ce48190a05f1d37f972c36c completed April 19, 2026, 3:51 a.m.
Created at: April 8, 2026, 9:28 p.m.