Triple

T14151878
Position Surface form Disambiguated ID Type / Status
Subject Rhea Seehorn E350702 entity
Predicate notableWork P4 FINISHED
Object Kim Wexler E408316 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: Kim Wexler | Statement: [Rhea Seehorn, notableWork, Kim Wexler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kim Wexler
Context triple: [Rhea Seehorn, notableWork, Kim Wexler]
  • A. Kim Wexler chosen
    Kim Wexler is a highly skilled and morally conflicted attorney whose complex relationship with Jimmy McGill/Saul Goodman is central to the character-driven drama of Better Call Saul.
  • B. Howard Hamlin
    Howard Hamlin is a high-powered, image-conscious attorney and partner at the law firm Hamlin, Hamlin & McGill in the television series "Better Call Saul."
  • C. Michael Ross
    Michael Ross was an American television writer and producer best known for co-creating influential sitcoms such as The Jeffersons.
  • D. Michael Ross
    Michael Ross is a film editor known for his work on the documentary "The True Cost," which examines the global impact of the fashion industry.
  • E. Saul Goodman
    Saul Goodman is a flamboyant, morally flexible criminal lawyer known for his shady legal tactics and comic relief in the Breaking Bad universe.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6124e23481909e5132a40a1d8624 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7ea34408190830263d7f5a88ce9 completed May 7, 2026, 8:36 p.m.
Created at: April 10, 2026, 12:57 a.m.