Triple

T4394101
Position Surface form Disambiguated ID Type / Status
Subject Janel Moloney E99440 entity
Predicate name P16 FINISHED
Object Janel Moloney E99440 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: Janel Moloney | Statement: [Janel Moloney, name, Janel Moloney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Janel Moloney
Context triple: [Janel Moloney, name, Janel Moloney]
  • A. Janel Moloney chosen
    Janel Moloney is an American actress best known for her role as Donna Moss on the political drama television series "The West Wing."
  • B. Nicole Shanahan
    Nicole Shanahan is an American attorney, legal tech entrepreneur, and philanthropist known for founding the patent management company ClearAccessIP and for her high-profile marriage to Google co-founder Sergey Brin.
  • C. Melissa Mathison
    Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
  • D. Kate Mullen
    Kate Mullen is the central protagonist of the work "Ransom," around whom the main narrative and its conflicts revolve.
  • E. Bridget Moynahan
    Bridget Moynahan is an American actress and model best known for her roles in films like "Coyote Ugly" and "I, Robot" and the TV series "Blue Bloods."
  • 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_69b345506b408190b0e3dee616738a7d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b352a9c8b88190a7894a40be4996f0 completed March 12, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf9ad2f8e48190aac71e657a9e1197 completed March 22, 2026, 7:31 a.m.
Created at: March 12, 2026, 11:20 p.m.