Triple

T15367835
Position Surface form Disambiguated ID Type / Status
Subject CHiPs (2017 film) E367462 entity
Predicate starring P1507 FINISHED
Object Jane Kaczmarek E240508 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: Jane Kaczmarek | Statement: [CHiPs (2017 film), starring, Jane Kaczmarek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jane Kaczmarek
Context triple: [CHiPs (2017 film), starring, Jane Kaczmarek]
  • A. Jane Kaczmarek chosen
    Jane Kaczmarek is an American actress best known for her Emmy-nominated role as Lois, the overbearing yet loving mother on the television series "Malcolm in the Middle."
  • B. Tracy Daszkiewicz
    Tracy Daszkiewicz is a British public health official known for her central role in managing the response to the 2018 Salisbury Novichok nerve agent poisoning.
  • C. Michelle Marciniak
    Michelle Marciniak is a former American point guard best known for starring under coach Pat Summitt at the University of Tennessee and later playing in the WNBA.
  • D. Kimberly Krysiuk
    Kimberly Krysiuk is a writer known for her work on the series "Baby Mama."
  • E. Barbara Kowalcyk
    Barbara Kowalcyk is a food safety advocate and public health expert known for her work to reform food regulation after her young son died from an E. coli infection.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4a7cdc8190b7b48c97e774c306 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb7921208190bbf4e1a01c6ec5ee completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 3:18 a.m.