Triple

T3206536
Position Surface form Disambiguated ID Type / Status
Subject Kristen Wiig E67174 entity
Predicate givenName P17 FINISHED
Object Kristen
Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
 E335804 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: Kristen | Statement: [Kristen Wiig, givenName, Kristen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kristen
Context triple: [Kristen Wiig, givenName, Kristen]
  • A. Kristen
    Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
  • B. Kristen
    Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
  • C. Kirsten
    Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
  • D. Kristin
    Kristin is the given name of the acclaimed British-French actress Kristin Scott Thomas, known for her roles in films such as "The English Patient" and "Four Weddings and a Funeral."
  • E. Kristin
    Kristin is one of the official mascots of the 1994 Winter Olympics held in Lillehammer, Norway.
  • 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: Kristen
Triple: [Kristen Wiig, givenName, Kristen]
Generated description
Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kristen
Target entity description: Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • A. Kristen
    Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
  • B. Kristen
    Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
  • C. Kirsten
    Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
  • D. Kristin
    Kristin is the given name of the acclaimed British-French actress Kristin Scott Thomas, known for her roles in films such as "The English Patient" and "Four Weddings and a Funeral."
  • E. Kristin
    Kristin is one of the official mascots of the 1994 Winter Olympics held in Lillehammer, Norway.
  • 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_69ad8589bd988190afa7ed2bdffb7b33 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaa56c21c8190b6aa7c56cb15ad56 completed March 8, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24bcf7b2481908bc52cfa71bd313c completed March 12, 2026, 5:14 a.m.
NEDg Description generation batch_69b24cb0c5f0819083ea589ded12ef3b completed March 12, 2026, 5:18 a.m.
NED2 Entity disambiguation (via description) batch_69b24d2ce888819087cc7c3f5db0e859 completed March 12, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:07 p.m.