Triple

T8300807
Position Surface form Disambiguated ID Type / Status
Subject Russian Wikiquote E194343 entity
Predicate hasSisterProject P14971 FINISHED
Object Russian Wikisource E194343 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: Russian Wikisource | Statement: [Russian Wikiquote, hasSisterProject, Russian Wikisource]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russian Wikisource
Context triple: [Russian Wikiquote, hasSisterProject, Russian Wikisource]
  • A. Russian Wikiquote chosen
    Russian Wikiquote is the Russian-language edition of Wikiquote, a free online compendium of sourced quotations, proverbs, and sayings.
  • B. Rus
    Rus was a medieval East Slavic cultural and political realm that laid the foundations for the modern nations of Russia, Ukraine, and Belarus.
  • C. Fundamental Library of Moscow State University
    The Fundamental Library of Moscow State University is the university’s main academic library and one of Russia’s largest research and educational library centers, supporting scholarship across a wide range of disciplines.
  • D. Russo
    Russo is an Italian surname commonly used as a variant of Rossi, often associated with people of Italian heritage.
  • E. The Russian
    The Russian is a thriller novel in James Patterson and James O. Born’s Michael Bennett series, in which the NYPD detective hunts a brutal serial killer targeting women across multiple cities.
  • 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_69ca82e50ebc81909aa7b260c76bd757 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7e879c588190a6f95cf7795541ad completed March 31, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd68bcb43081909e3a8a00947d03f2 completed April 1, 2026, 6:49 p.m.
Created at: March 30, 2026, 5:53 p.m.