Triple

T5943501
Position Surface form Disambiguated ID Type / Status
Subject Jelgava E132222 entity
Predicate hasTwinTown P919 FINISHED
Object Ivanovo E419902 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: Ivanovo | Statement: [Jelgava, hasTwinTown, Ivanovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ivanovo
Context triple: [Jelgava, hasTwinTown, Ivanovo]
  • A. Balashov
    Balashov is a town in southwestern Russia that serves as an important local administrative and transportation center within Saratov Oblast.
  • B. Balakovo
    Balakovo is a city in Russia’s Saratov Oblast known as an industrial and energy hub on the Volga River.
  • C. Ryazan
    Ryazan is a historic city in western Russia known for its medieval kremlin, role as a regional cultural and economic center, and legacy as one of the country’s oldest urban settlements.
  • D. Ivanovo Oblast chosen
    Ivanovo Oblast is a region in central Russia known historically for its textile industry and often referred to as part of the country’s “Golden Ring” of ancient cities.
  • E. Oryol
    Oryol was a notable warship of the Imperial Russian Navy, recognized for its role in Russia’s early modern naval 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0393641d0819081c6c44816d94e4e completed March 22, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c07f9ab081909fe7727837fa7f7a completed March 23, 2026, 4:24 a.m.
Created at: March 22, 2026, 4:01 p.m.