Triple

T13217965
Position Surface form Disambiguated ID Type / Status
Subject Philippa Giles E314670 entity
Predicate notableWork P4 FINISHED
Object Luther E717115 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: [Philippa Giles, notableWork, Luther]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luther
Context triple: [Philippa Giles, notableWork, Luther]
  • A. Luther
    Luther is a British psychological crime drama television series starring Idris Elba as a brilliant but troubled detective.
  • B. 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.
  • C. Luther
    Luther is a common German surname most famously associated with the Protestant Reformer Martin Luther and his family.
  • D. Luther
    Luther is a small town in central Oklahoma, United States, known for its rural character and location along historic Route 66.
  • E. Luther chosen
    Luther is a 1961 stage play by British dramatist John Osborne that dramatizes the life and religious struggles of Protestant Reformation leader Martin Luther.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf392e08190949ee4d194566395 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff2085f88190be8cfc309d21f9cb completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:18 p.m.