Triple

T20029357
Position Surface form Disambiguated ID Type / Status
Subject Happythankyoumoreplease E495079 entity
Predicate hasCastMember P2308 FINISHED
Object Kate Mara 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: Kate Mara | Statement: [Happythankyoumoreplease, hasCastMember, Kate Mara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Mara
Context triple: [Happythankyoumoreplease, hasCastMember, Kate Mara]
  • A. Kate Mara chosen
    Kate Mara is an American actress known for her roles in films like "The Martian" and "Brokeback Mountain" and TV series such as "House of Cards."
  • B. Penelope Ann Miller
    Penelope Ann Miller is an American actress known for her roles in films such as "Carlito's Way," "The Artist," and "Kindergarten Cop."
  • C. Roxann Dawson
    Roxann Dawson is an American actress and director best known for playing Chief Engineer B'Elanna Torres on the television series Star Trek: Voyager.
  • D. Ashley Johnson
    Ashley Johnson is an American actress and voice actress known for her roles in television, film, and video games, including voicing Ellie in "The Last of Us" series.
  • E. Zoe Saldana
    Zoe Saldana is an American actress known for her prominent roles in major science fiction and fantasy franchises, including Star Trek, Avatar, and the Marvel Cinematic Universe.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662908df081909a6c8ccf0dd90fff completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:36 p.m.