Triple

T10083922
Position Surface form Disambiguated ID Type / Status
Subject Saskia Reeves E213971 entity
Predicate notableWork P4 FINISHED
Object Luther E38385 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: Luther | Statement: [Saskia Reeves, notableWork, Luther]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luther
Context triple: [Saskia Reeves, notableWork, Luther]
  • A. Luther
    Luther is a masculine given name of Germanic origin, most famously borne by civil rights leader Martin Luther King Jr. and R&B singer Luther Vandross.
  • B. Luther chosen
    Luther is a British psychological crime drama television series starring Idris Elba as a brilliant but troubled detective.
  • C. Luther
    Luther is a small town in central Oklahoma, United States, known for its rural character and location along historic Route 66.
  • D. Luther
    Luther is a 1961 stage play by British dramatist John Osborne that dramatizes the life and religious struggles of Protestant Reformation leader Martin Luther.
  • E. Luther
    Luther is a common German surname most famously associated with the Protestant Reformer Martin Luther and his family.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd044c1ec8190b5b48cdb0584d00c completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b675f4b08190bd8285f210191b93 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.