Triple

T4939219
Position Surface form Disambiguated ID Type / Status
Subject Francis, Duke of Saxe-Coburg-Saalfeld E110886 entity
Predicate givenName P17 FINISHED
Object Franz E112851 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 | Statement: [Francis, Duke of Saxe-Coburg-Saalfeld, givenName, Franz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franz
Context triple: [Francis, Duke of Saxe-Coburg-Saalfeld, givenName, Franz]
  • A. Franz
    Franz is a character in Louisa May Alcott's novel "Little Men," one of the boys at Plumfield School whose experiences reflect the book's themes of growth, education, and moral development.
  • B. Franz chosen
    Franz is the given name of Franz Cardinal König, a prominent 20th-century Austrian Catholic cardinal and influential church leader.
  • C. Alois
    Alois is a masculine given name of Germanic origin, notably borne by Alois Hitler, the father of Adolf Hitler.
  • D. Nikolaus
    Nikolaus is the traditional German figure based on Saint Nicholas who brings small gifts to children on the eve of December 6th.
  • E. Gustav
    Gustav is a masculine given name of German origin, borne by several notable historical figures including scientists, artists, and royalty.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7088f6e48190bf09e58ab053a4d1 completed March 20, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba512f1881909e9bf062fe416ac8 completed March 21, 2026, 3:33 p.m.
Created at: March 20, 2026, 1:31 p.m.