Triple

T8446157
Position Surface form Disambiguated ID Type / Status
Subject Clemm E199680 entity
Predicate relatedName P3889 FINISHED
Object Klemens E111656 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: Klemens | Statement: [Clemm, relatedName, Klemens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klemens
Context triple: [Clemm, relatedName, Klemens]
  • A. Klemens chosen
    Klemens is a given name, primarily used in German-speaking and Central European countries, that corresponds to the Latin-derived name Clemens.
  • B. Ottmar
    Ottmar is a German former football player and highly successful manager best known for leading Borussia Dortmund and Bayern Munich to numerous domestic and European titles.
  • C. Karl Joseph
    Karl Joseph was the given name of Archduke Charles Joseph of Austria, a Habsburg archduke of the 18th century.
  • D. Charles Dagomer
    Charles Dagomer was an 18th-century French artist and teacher known for instructing painter Jean-Baptiste Huet.
  • E. Franz Clement
    Franz Clement was an Austrian violinist, conductor, and composer of the early 19th century, renowned in his time as a virtuoso and closely associated with the music of Ludwig van Beethoven.
  • 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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe3152a3c819092efdeab718def7a completed March 31, 2026, 3:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1db6330c81909c853c453fddf3c5 completed April 2, 2026, 7:41 a.m.
Created at: March 30, 2026, 6:09 p.m.