Triple

T19703622
Position Surface form Disambiguated ID Type / Status
Subject VisualEditor E473154 entity
Predicate usedBy P260 FINISHED
Object Japanese 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: Japanese Wikipedia | Statement: [VisualEditor, usedBy, Japanese Wikipedia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japanese Wikipedia
Context triple: [VisualEditor, usedBy, Japanese Wikipedia]
  • A. Japanese Wikipedia chosen
    Japanese Wikipedia is the Japanese-language edition of the free, collaboratively edited online encyclopedia Wikipedia.
  • B. Japanese Wikiversity
    Japanese Wikiversity is the Japanese-language edition of Wikiversity, a Wikimedia project that provides free educational resources and supports collaborative learning and teaching.
  • C. Japanese Wikinews
    Japanese Wikinews is the Japanese-language edition of the Wikinews project, a collaboratively written, free-content news source.
  • D. Japanese Wikibooks
    Japanese Wikibooks is the Japanese-language edition of Wikibooks, a Wikimedia Foundation project that hosts collaboratively written open-content textbooks and instructional materials.
  • E. Japanese Wikisource
    Japanese Wikisource is the Japanese-language edition of Wikisource, a free online digital library of public domain and freely licensed texts.
  • 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e642b8707081908fbf96c989d2d52d completed April 20, 2026, 3:14 p.m.
Created at: April 10, 2026, 1:46 p.m.