Triple

T2972871
Position Surface form Disambiguated ID Type / Status
Subject Karl Benz E80320 entity
Predicate residence P75 FINISHED
Object Ladenburg E314920 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: Ladenburg | Statement: [Karl Benz, residence, Ladenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ladenburg
Context triple: [Karl Benz, residence, Ladenburg]
  • A. Ladenburg chosen
    Ladenburg is a historic town in southwestern Germany known for its well-preserved old town and its association with automobile pioneer Karl Benz.
  • B. Löwenthal
    Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
  • C. Furth
    A Furth is a mountain in the British Isles outside Scotland that meets the height and prominence criteria to be classified similarly to a Scottish Munro.
  • D. Neu-Anspach
    Neu-Anspach is a small town in the Hochtaunus district of Hesse, Germany, known for its proximity to the Taunus mountains and the open-air museum Hessenpark.
  • E. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • 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_69ad8b14ffe881908ffed62f9595c867 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad998656948190ba79d7196d735f34 completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108e3db5481908c0fac0f48fb8fe2 completed March 11, 2026, 6:17 a.m.
Created at: March 8, 2026, 2:58 p.m.