Triple

T10876654
Position Surface form Disambiguated ID Type / Status
Subject Insterburg E256815 entity
Predicate renamedAs P65 FINISHED
Object Chernyakhovsk E899194 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: Chernyakhovsk | Statement: [Insterburg, renamedAs, Chernyakhovsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chernyakhovsk
Context triple: [Insterburg, renamedAs, Chernyakhovsk]
  • A. Chernyakhovsk chosen
    Chernyakhovsk is a town in Russia’s Kaliningrad Oblast, known historically as the former East Prussian city of Insterburg.
  • B. Chervonohrad
    Chervonohrad is a mining and industrial city in western Ukraine known for its coal industry and location in the Lviv Oblast.
  • C. Cherkassk
    Cherkassk was a historic Cossack town that served as an early administrative and cultural center in the Don region of southern Russia.
  • D. Černilov
    Černilov is a municipality and village in the Hradec Králové Region of the Czech Republic, known for its rural character and proximity to the city of Hradec Králové.
  • E. Yukhnov
    Yukhnov is a small historic town in western Russia known for its location on the Ugra River and its role in regional trade and World War II history.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751ac901881909938cabe4d21bdbf completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3c7e869748190991e06d9df50faa9 completed April 18, 2026, 6:05 p.m.
Created at: April 8, 2026, 9:21 p.m.