Triple

T14840326
Position Surface form Disambiguated ID Type / Status
Subject Amanda Donohoe E348943 entity
Predicate hasWorkedWith P9615 FINISHED
Object Jill Eikenberry E560084 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: Jill Eikenberry | Statement: [Amanda Donohoe, hasWorkedWith, Jill Eikenberry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jill Eikenberry
Context triple: [Amanda Donohoe, hasWorkedWith, Jill Eikenberry]
  • A. Jill Eikenberry chosen
    Jill Eikenberry is an American actress best known for her Emmy-nominated role as attorney Ann Kelsey on the television series "L.A. Law."
  • B. Loretta Swit
    Loretta Swit is an American actress best known for her Emmy-winning role as Major Margaret "Hot Lips" Houlihan on the television series M*A*S*H.
  • C. Joan Allen
    Joan Allen is an acclaimed American actress known for her versatile performances in film, television, and theater, including prominent roles in dramas and political thrillers.
  • D. Kelly Rutherford
    Kelly Rutherford is an American actress best known for her roles on television series such as "Melrose Place" and "Gossip Girl."
  • E. Deborah Rush
    Deborah Rush is an American actress known for her character roles in film, television, and theater, including appearances in comedies and independent productions.
  • 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded28e40f08190b309d8ac6404d2fc completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff2ce5d0708190bbfff5d68c5e7a3c completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 1:53 a.m.