Triple

T12790275
Position Surface form Disambiguated ID Type / Status
Subject Vladimir Kramnik E305740 entity
Predicate placeOfBirth P1 FINISHED
Object Tuapse E195806 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: Tuapse | Statement: [Vladimir Kramnik, placeOfBirth, Tuapse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuapse
Context triple: [Vladimir Kramnik, placeOfBirth, Tuapse]
  • A. Tuapse chosen
    Tuapse is a Black Sea port town in southern Russia known as a seaside resort and industrial center within Krasnodar Krai.
  • B. Severomorsk
    Severomorsk is a closed naval town in Russia’s Murmansk Oblast that serves as the main base of the Russian (formerly Soviet) Northern Fleet on the Barents Sea.
  • C. Sestroretsk
    Sestroretsk is a town in northwestern Russia, now part of Saint Petersburg, historically known for its arms factory and seaside resort area on the Gulf of Finland.
  • D. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • E. Tosno
    Tosno is a town in northwestern Russia that serves as an administrative and transportation hub southeast of Saint Petersburg.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6a61f48190972e241e70bc392c completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0dd657c8190b69e8bf187034360 completed May 3, 2026, 3:28 a.m.
Created at: April 9, 2026, 5:30 p.m.