Triple

T18404096
Position Surface form Disambiguated ID Type / Status
Subject Kelli Giddish E450073 entity
Predicate notableRole P22 FINISHED
Object Amanda Rollins NE NERFINISHED

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: Amanda Rollins | Statement: [Kelli Giddish, notableRole, Amanda Rollins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amanda Rollins
Context triple: [Kelli Giddish, notableRole, Amanda Rollins]
  • A. Amanda Rollins chosen
    Amanda Rollins is a fictional NYPD detective on Law & Order: Special Victims Unit who works closely with Olivia Benson on sex-crimes investigations.
  • B. Amanda Clayton
    Amanda Clayton is an American actress best known for her role in the crime drama television series "City on a Hill."
  • C. Amanda Brown
    Amanda Brown is an Australian musician best known as the multi-instrumentalist and violinist for the indie rock band The Go-Betweens.
  • D. Amanda Thompson
    Amanda Thompson is a prominent member of the Thompson family, known for her public profile and contributions that have brought recognition to the family name.
  • E. Amanda Kramer
    Amanda Kramer is an American filmmaker and writer known for her stylized, genre-bending independent films and theatrical, performance-driven storytelling.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e5195509cc8190bd4e91adb9b4a0ce completed April 19, 2026, 6:05 p.m.
Created at: April 10, 2026, 10:46 a.m.