Triple

T15673173
Position Surface form Disambiguated ID Type / Status
Subject Beno Gutenberg E377369 entity
Predicate givenName P17 FINISHED
Object Beno E377369 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: Beno | Statement: [Beno Gutenberg, givenName, Beno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beno
Context triple: [Beno Gutenberg, givenName, Beno]
  • A. Beno chosen
    Beno is the given name of the German seismologist Beno Gutenberg, known for his pioneering work on the structure of the Earth's interior.
  • B. Benais
    Benais is a French commune in the Indre-et-Loire department of the Loire Valley, known for its vineyards and wine production.
  • C. Béraud
    Béraud is a French surname most notably associated with the 19th-century painter Jean Béraud, renowned for his vivid depictions of Parisian life during the Belle Époque.
  • D. Bernardin
    Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
  • E. Bonan
    Bonan is a Mongolic ethnic group in China, primarily residing in Gansu and Qinghai provinces, known for their distinct language and blend of Islamic and local cultural traditions.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2c996c8190a9ebe0e92608feaa completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6edb12bc8190b2c5558190671ae5 completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:16 a.m.