Triple

T11373509
Position Surface form Disambiguated ID Type / Status
Subject Eduard Bloch E269403 entity
Predicate givenName P17 FINISHED
Object Eduard E830385 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: Eduard | Statement: [Eduard Bloch, givenName, Eduard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eduard
Context triple: [Eduard Bloch, givenName, Eduard]
  • A. Eduard
    Eduard was the younger son of physicist Albert Einstein, known for his promising studies in psychiatry and his lifelong struggle with schizophrenia.
  • B. Eduard
    Eduard is one of the central protagonists in Johann Wolfgang von Goethe’s novel "Elective Affinities," whose actions and relationships drive the story’s exploration of passion, marriage, and moral conflict.
  • C. Eduard
    Eduard "Del" Delacroix is a fictional death row inmate from Stephen King's novel "The Green Mile," known for his close bond with a pet mouse and his tragic execution.
  • D. Eduard chosen
    Eduard is a masculine given name of German origin, commonly used in various European countries.
  • E. Eduard
    Eduard is a central character in Paulo Coelho’s novel "Veronika Decides to Die," portrayed as a sensitive, introspective young man whose relationship with the protagonist profoundly influences her view of life and death.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea8d244c8190b865260338edb532 completed April 9, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d32db0d081908f5a8f6ca1357997 completed April 20, 2026, 7:18 a.m.
Created at: April 8, 2026, 9:33 p.m.