Triple

T8156176
Position Surface form Disambiguated ID Type / Status
Subject Their Finest E190454 entity
Predicate castMember P1668 FINISHED
Object Rachael Stirling E524716 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: Rachael Stirling | Statement: [Their Finest, castMember, Rachael Stirling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachael Stirling
Context triple: [Their Finest, castMember, Rachael Stirling]
  • A. Rachael Stirling chosen
    Rachael Stirling is a British actress known for her work in television, film, and theatre, including prominent roles in series such as "Detectorists" and "Tipping the Velvet."
  • B. Rachael MacFarlane
    Rachael MacFarlane is an American voice actress and singer best known for her work on animated television series, including voicing Hayley Smith on "American Dad!"
  • C. Rachael Taylor
    Rachael Taylor is an Australian actress known for her roles in films like "Transformers" and TV series such as "Jessica Jones."
  • D. Bridget Christie
    Bridget Christie is a British stand-up comedian, writer, and actress known for her sharp, often feminist-leaning comedy and acclaimed radio and television work.
  • E. Suzanne Mackie
    Suzanne Mackie is a British television and film producer known for her work on acclaimed projects such as "The Crown" and other high-profile UK dramas.
  • 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb44d8a37481909397b5cc321b94be completed March 31, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde71b7688819096b2d30a37a8a00b completed April 2, 2026, 3:48 a.m.
Created at: March 30, 2026, 5:37 p.m.