Triple

T19328252
Position Surface form Disambiguated ID Type / Status
Subject Bertha E483415 entity
Predicate hasNotableBearer P458 FINISHED
Object Bertha Benz NE NERFINISHED

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: Bertha Benz | Statement: [Bertha, hasNotableBearer, Bertha Benz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bertha Benz
Context triple: [Bertha, hasNotableBearer, Bertha Benz]
  • A. Bertha Benz chosen
    Bertha Benz was a German automotive pioneer best known for undertaking the first long-distance automobile journey in 1888, which proved the practicality of her husband Karl Benz’s invention and helped launch the modern car industry.
  • B. Bertha Maybach
    Bertha Maybach was the wife of German engineer and automobile pioneer Wilhelm Maybach, associated with the early history of the automotive industry.
  • C. Clara Benz
    Clara Benz was one of the children of German engineer and automobile pioneer Karl Benz.
  • D. Karl Benz
    Karl Benz was a pioneering German engineer and inventor widely credited with creating the first practical automobile powered by an internal combustion engine.
  • E. Eugen Benz
    Eugen Benz was one of the sons of automobile pioneer Karl Benz and a member of the family associated with the early development of the automotive industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e6163f32f48190be17cccf4e537372 completed April 20, 2026, 12:04 p.m.
Created at: April 10, 2026, 1:33 p.m.