Triple

T14678108
Position Surface form Disambiguated ID Type / Status
Subject Chaim Ozer Grodzinski E344700 entity
Predicate residence P75 FINISHED
Object Vilna E271703 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: Vilna | Statement: [Chaim Ozer Grodzinski, residence, Vilna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vilna
Context triple: [Chaim Ozer Grodzinski, residence, Vilna]
  • A. Vilna chosen
    Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of the region.
  • B. Mitau
    Mitau, historically known as the capital of the Duchy of Courland and Semigallia, is the former German name for the city now called Jelgava in present-day Latvia.
  • C. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • D. Novopolotsk
    Novopolotsk is an industrial city in northern Belarus known for its major oil refinery and petrochemical complex.
  • E. Polotsk
    Polotsk is one of the oldest cities in Belarus, historically a major political, cultural, and religious center of the medieval East Slavic world.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb567c2b88190a9639e61b6fba7df completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf07e355881908a2e75ccff4f0590 completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:27 a.m.