Triple

T13838882
Position Surface form Disambiguated ID Type / Status
Subject Black Monday E332597 entity
Predicate hasMainCharacter P1183 FINISHED
Object Tiff Georgina
Tiff Georgina is a fictional character from the dark comedy television series "Black Monday," which satirizes Wall Street culture in the 1980s.
 E1063787 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: Tiff Georgina | Statement: [Black Monday, hasMainCharacter, Tiff Georgina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tiff Georgina
Context triple: [Black Monday, hasMainCharacter, Tiff Georgina]
  • A. Tiffani
    Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
  • B. Georgina Kirrin
    Georgina "George" Kirrin is a spirited, tomboyish girl and one of the central child protagonists in Enid Blyton's classic "Famous Five" adventure series.
  • 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 a character portrayed by actress and comedian Melissa Rauch, known for her energetic and distinctive vocal performances.
  • E. Tina
    Tina is a feminine given name commonly used in English-speaking countries, often as a diminutive of names like Christina, Martina, or Valentina.
  • 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: Tiff Georgina
Triple: [Black Monday, hasMainCharacter, Tiff Georgina]
Generated description
Tiff Georgina is a fictional character from the dark comedy television series "Black Monday," which satirizes Wall Street culture in the 1980s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tiff Georgina
Target entity description: Tiff Georgina is a fictional character from the dark comedy television series "Black Monday," which satirizes Wall Street culture in the 1980s.
  • A. Tiffani
    Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
  • B. Georgina Kirrin
    Georgina "George" Kirrin is a spirited, tomboyish girl and one of the central child protagonists in Enid Blyton's classic "Famous Five" adventure series.
  • 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 a feminine given name commonly used in English-speaking countries, often as a diminutive of names like Christina, Martina, or Valentina.
  • E. Tina
    Tina is a character portrayed by actress and comedian Melissa Rauch, known for her energetic and distinctive vocal performances.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02ac6b7c81908d44632d6d628339 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8f630d081909439e1cdc5d60430 completed May 3, 2026, 9:07 p.m.
NEDg Description generation batch_69f7bb3bb7288190b981a9439304124d completed May 3, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69f7bbac5a148190990ac56759e527cd completed May 3, 2026, 9:18 p.m.
Created at: April 9, 2026, 10:13 p.m.