Triple

T20243789
Position Surface form Disambiguated ID Type / Status
Subject Yitzhak Tabenkin E498368 entity
Predicate placeOfBirth P1 FINISHED
Object Babruysk 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: Babruysk | Statement: [Yitzhak Tabenkin, placeOfBirth, Babruysk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Babruysk
Context triple: [Yitzhak Tabenkin, placeOfBirth, Babruysk]
  • A. Babruysk chosen
    Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
  • B. Novogrudok
    Novogrudok is a historic town in western Belarus known as one of the early political centers of the Grand Duchy of Lithuania.
  • C. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • D. Kobryn
    Kobryn is a historic town in southwestern Belarus known for its location at the confluence of the Mukhavets and Dnieper–Bug Canal and its role as a regional cultural and economic center.
  • E. Baranavichy
    Baranavichy is a significant industrial and railway hub city in western Belarus.
  • 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e67170aa248190922fc845d2265ae3 completed April 20, 2026, 6:33 p.m.
Created at: April 11, 2026, 11:40 p.m.