Triple

T10258516
Position Surface form Disambiguated ID Type / Status
Subject Johannes Gutenberg E240535 entity
Predicate name P16 FINISHED
Object Johannes Gutenberg E240535 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: Johannes Gutenberg | Statement: [Johannes Gutenberg, name, Johannes Gutenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johannes Gutenberg
Context triple: [Johannes Gutenberg, name, Johannes Gutenberg]
  • A. Johannes Gutenberg chosen
    Johannes Gutenberg was a 15th-century German inventor and printer credited with introducing movable-type printing to Europe, revolutionizing the spread of information.
  • B. Anton Koberger
    Anton Koberger was a prominent 15th-century German printer and publisher, best known for producing the richly illustrated Nuremberg Chronicle.
  • C. Erich Gutenberg
    Erich Gutenberg was a prominent German economist and business administration scholar known for fundamentally shaping modern German management theory and production economics.
  • D. William Caxton
    William Caxton was a 15th-century English merchant, diplomat, and printer best known for introducing the printing press to England and producing some of the first books printed in English.
  • E. Guttenberg
    Guttenberg is a surname most famously associated with American actor and comedian Steve Guttenberg, known for his roles in 1980s films such as the Police Academy series.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d24de4588190b68fb3daa36dbd7d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7e9a9d48190865f047750d7bc6c completed April 9, 2026, 12:50 a.m.
Created at: April 6, 2026, 11:31 a.m.