Triple

T2054909
Position Surface form Disambiguated ID Type / Status
Subject Kirsten Gillibrand E45651 entity
Predicate givenName P17 FINISHED
Object Kirsten
Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
E228757 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: Kirsten | Statement: [Kirsten Gillibrand, givenName, Kirsten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirsten
Context triple: [Kirsten Gillibrand, givenName, Kirsten]
  • 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. Kristin
    Kristin is one of the official mascots of the 1994 Winter Olympics held in Lillehammer, Norway.
  • C. Kathryn
    Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
  • D. Kirsten Mehr
    Kirsten Mehr is the German-born wife of British politician and former UKIP leader Nigel Farage.
  • E. Karin
    Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
  • 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: Kirsten
Triple: [Kirsten Gillibrand, givenName, Kirsten]
Generated description
Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kirsten
Target entity description: Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
  • 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. Kristin
    Kristin is one of the official mascots of the 1994 Winter Olympics held in Lillehammer, Norway.
  • C. Kathryn
    Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
  • D. Kirsten Mehr
    Kirsten Mehr is the German-born wife of British politician and former UKIP leader Nigel Farage.
  • E. Karin
    Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
  • 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_69a8891a19508190a12ef1e192308dcb completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9a8518081909ba95a8ef9321f12 completed March 7, 2026, 5:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae200eb09881908bbfe47ebb62f55e completed March 9, 2026, 1:19 a.m.
NEDg Description generation batch_69ae20cb479c8190853d0d954af16887 completed March 9, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_69ae21614e74819093617a355f0857c8 completed March 9, 2026, 1:24 a.m.
Created at: March 4, 2026, 7:40 p.m.