Triple

T14786864
Position Surface form Disambiguated ID Type / Status
Subject Franz Ruff E347549 entity
Predicate name P16 FINISHED
Object Franz Ruff E347549 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: Franz Ruff | Statement: [Franz Ruff, name, Franz Ruff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franz Ruff
Context triple: [Franz Ruff, name, Franz Ruff]
  • A. Franz Ruff chosen
    Franz Ruff was a German architect associated with the Nazi era, known for his work on monumental projects such as the Nuremberg party rally grounds.
  • B. Franz von Walsegg
    Franz von Walsegg was an Austrian count and amateur musician best known for anonymously commissioning Mozart’s Requiem, which he intended to pass off as his own composition.
  • C. Franz Tunder
    Franz Tunder was a 17th-century German organist and composer, noted as a key predecessor of the North German organ school later exemplified by his successor and son-in-law Dieterich Buxtehude.
  • D. Wolfgang Zillig
    Wolfgang Zillig was a German microbiologist and virologist known for his pioneering work on extremophilic archaea and their viruses.
  • E. Franz Eckert
    Franz Eckert was a German musician and composer known for arranging and influencing early modern national anthems in Japan and Korea.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decaa083e481908336d58d026eec32 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b9e8a08190bc736ac207b77324 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.