Triple

T21654491
Position Surface form Disambiguated ID Type / Status
Subject Boris Savinkov E534421 entity
Predicate placeOfBirth P1 FINISHED
Object Kharkov 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: Kharkov | Statement: [Boris Savinkov, placeOfBirth, Kharkov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kharkov
Context triple: [Boris Savinkov, placeOfBirth, Kharkov]
  • A. Kharkiv chosen
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • B. Kherson
    Kherson is a port city in southern Ukraine near the Black Sea, historically significant as a shipbuilding and industrial center and strategically important due to its location on the Dnieper River.
  • C. Kyiv
    Kyiv is the capital and largest city of Ukraine, serving as its political, cultural, and economic center.
  • D. Dnipro
    Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
  • E. Kremenchuk
    Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
  • 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_69e0c466aec88190ba39c7543dbc8ba2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef59176b28819092384fc5f8968022 completed April 27, 2026, 12:39 p.m.
Created at: April 16, 2026, 6:36 p.m.