Triple

T2882008
Position Surface form Disambiguated ID Type / Status
Subject Gina Gershon E59417 entity
Predicate givenName P17 FINISHED
Object Gina
Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
 E307997 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: Gina | Statement: [Gina Gershon, givenName, Gina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gina
Context triple: [Gina Gershon, givenName, Gina]
  • A. Gianna
    Gianna is a feminine given name of Italian origin, often associated with the late Gianna Bryant, daughter of basketball legend Kobe Bryant.
  • B. Jenna
    Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
  • C. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • D. Tina
    Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
  • E. Sandra
    Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • 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: Gina
Triple: [Gina Gershon, givenName, Gina]
Generated description
Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gina
Target entity description: Gina is a feminine given name commonly used in English and Italian-speaking countries, often as a short form of names like Regina, Georgina, or Luigina.
  • A. Gianna
    Gianna is a feminine given name of Italian origin, often associated with the late Gianna Bryant, daughter of basketball legend Kobe Bryant.
  • B. Jenna
    Jenna is a common feminine given name, often used as a diminutive or variant of Jennifer.
  • C. Tina
    Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
  • D. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • E. Sandra
    Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe02aa5948190a2e0bd9168232bd5 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b031633efc819088c2ea29eafaff0f completed March 10, 2026, 2:57 p.m.
NEDg Description generation batch_69b033894ca881908691b88e6108257c completed March 10, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_69b03c3af7b48190b66bb32df59196e3 completed March 10, 2026, 3:43 p.m.
Created at: March 6, 2026, 10:03 p.m.