Triple

T3233277
Position Surface form Disambiguated ID Type / Status
Subject Heinrich Bullinger E67791 entity
Predicate influencedBy P9 FINISHED
Object Martin Luther E8525 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: Martin Luther | Statement: [Heinrich Bullinger, influencedBy, Martin Luther]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Martin Luther
Context triple: [Heinrich Bullinger, influencedBy, Martin Luther]
  • A. Martin Luther chosen
    Martin Luther was a 16th-century German theologian and key figure of the Protestant Reformation whose teachings challenged Catholic doctrine and reshaped Western Christianity.
  • B. Martin Franz Luther
    Martin Franz Luther was a German Nazi diplomat and SS official who served in the Foreign Office and participated in the administration of the Holocaust.
  • C. 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.
  • D. Luther
    Luther is a common German surname most famously associated with the Protestant Reformer Martin Luther and his family.
  • E. Luther
    Luther is a British psychological crime drama television series starring Idris Elba as a brilliant but troubled detective.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaedb718c8190aae12f763033713a completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2773b494c8190a2c0c5042e8eaa55 completed March 12, 2026, 8:20 a.m.
Created at: March 8, 2026, 3:08 p.m.