Triple

T20323863
Position Surface form Disambiguated ID Type / Status
Subject Daniel Risch E492280 entity
Predicate hasBiographyIn P5385 FINISHED
Object German Wikipedia 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: German Wikipedia | Statement: [Daniel Risch, hasBiographyIn, German Wikipedia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: German Wikipedia
Context triple: [Daniel Risch, hasBiographyIn, German Wikipedia]
  • A. German Wikipedia chosen
    German Wikipedia is the German-language edition of the free, collaboratively edited online encyclopedia Wikipedia.
  • B. German Wikisource
    German Wikisource is the German-language edition of Wikisource, a Wikimedia project that provides a free online library of public domain and freely licensed source texts.
  • C. German Wiktionary
    German Wiktionary is the German-language edition of the collaborative, multilingual online dictionary project Wiktionary, providing definitions, translations, and linguistic information for words and phrases.
  • D. German Wikiversity
    German Wikiversity is the German-language edition of Wikiversity, a Wikimedia project dedicated to free educational resources and collaborative learning.
  • E. German Wikibooks
    German Wikibooks is the German-language edition of the Wikibooks project, offering collaboratively written, open-content textbooks and learning materials.
  • 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_69e0b4a0134081909113563e1c3ba68a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6778e59508190bfd7a3ce44d56a93 completed April 20, 2026, 6:59 p.m.
Created at: April 16, 2026, 11:21 a.m.