Triple

T9485795
Position Surface form Disambiguated ID Type / Status
Subject Kirsten Gillibrand E228757 entity
Predicate givenName P17 FINISHED
Object Kirsten E228757 NE FINISHED

How this triple was built (2 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. Kirsten chosen
    Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
  • B. Kristen
    Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
  • C. 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.
  • D. Kristen
    Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • E. Kristin
    Kristin is a feminine given name commonly used in English-speaking and Scandinavian countries, often considered a variant of Christine or Christina.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca84730a5081908de282651019bf2f completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd804fb2b4819084c7f5a842dbe5a6 completed April 1, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d1326b8819084c6d9490b7a96dc completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:55 p.m.