Triple

T12569532
Position Surface form Disambiguated ID Type / Status
Subject Staritsky Uyezd E295563 entity
Predicate administrativeCenter P1474 FINISHED
Object Staritsa E576596 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: Staritsa | Statement: [Staritsky Uyezd, administrativeCenter, Staritsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Staritsa
Context triple: [Staritsky Uyezd, administrativeCenter, Staritsa]
  • A. Staritsa chosen
    Staritsa is a historic town in Tver Oblast, Russia, known for its medieval monasteries and role as a regional center in the upper Volga region.
  • B. Yazhelbitsy
    Yazhelbitsy is a rural locality in Russia known for its proximity to Mount Uzhin.
  • C. Bogdanovka
    Bogdanovka is a village in Ukraine known as the site of a World War II massacre of Jews and now commemorated as a Holocaust memorial location.
  • D. Terekhovo
    Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
  • E. Luzhitsy
    Luzhitsy is a rural village in northwestern Russia historically associated with the Votic people and their traditional language and culture.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d954a422c88190a22cc34d2eac00ce completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbb096d881908dfd2a7126632d96 completed May 3, 2026, 4:14 a.m.
Created at: April 8, 2026, 11:50 p.m.