Triple

T16683733
Position Surface form Disambiguated ID Type / Status
Subject Kristy Swanson E405404 entity
Predicate givenName P17 FINISHED
Object Kristen E335804 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: Kristen | Statement: [Kristy Swanson, givenName, Kristen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristen
Context triple: [Kristy Swanson, 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. Kristen chosen
    Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • D. Kristen
    Kristen is the central protagonist of the psychological horror film "The Ward," around whom the mysterious and unsettling events of the story revolve.
  • E. Kirsten
    Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37d70d3f8819087d1bd700c94a83f completed April 18, 2026, 12:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a422f8c8190873fd7089df8fbd4 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.