Triple

T20215021
Position Surface form Disambiguated ID Type / Status
Subject ER E493594 entity
Predicate portrayedBy P1507 FINISHED
Object Maura Tierney 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: Maura Tierney | Statement: [ER, portrayedBy, Maura Tierney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maura Tierney
Context triple: [ER, portrayedBy, Maura Tierney]
  • A. Maura Tierney chosen
    Maura Tierney is an American actress best known for her roles on the television series "ER" and "NewsRadio," as well as in various film and stage productions.
  • B. Melissa Fitzgerald
    Melissa Fitzgerald is an American actress and social activist best known for her role as Carol Fitzpatrick on the television series "The West Wing" and for her leadership work with the nonprofit Justice For Vets.
  • C. Mary-Louise Parker
    Mary-Louise Parker is an American actress best known for her roles in the television series "Weeds" and numerous acclaimed film and stage performances.
  • D. Elizabeth Berkley
    Elizabeth Berkley is an American actress best known for her roles in the TV series "Saved by the Bell" and the film "Showgirls."
  • E. Téa Leoni
    Téa Leoni is an American actress and producer best known for her leading roles in film and television, including the political drama series "Madam Secretary."
  • 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66ed8101081908e53a8bde48624b1 completed April 20, 2026, 6:22 p.m.
Created at: April 11, 2026, 11:38 p.m.