Triple

T15690499
Position Surface form Disambiguated ID Type / Status
Subject Bobruysk offensive E380314 entity
Predicate location P40 FINISHED
Object Bobruysk E295542 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: Bobruysk | Statement: [Bobruysk offensive, location, Bobruysk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bobruysk
Context triple: [Bobruysk offensive, location, Bobruysk]
  • 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. Moghiliov-Podolsk
    Moghiliov-Podolsk is the Romanian name for Mogilev-Podilskyi, a city in western Ukraine located on the Dniester River near the border with Moldova.
  • D. Borisoglebsk
    Borisoglebsk is a small Russian city known for its historical architecture and location on the Vorona River in southwestern Russia.
  • E. Slutsk
    Slutsk is a historic town in central Belarus known for its role as a regional center and for its traditional Slutsk belts.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4e59988190aaf12f6a07c8f0e4 completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0335a0c8190ade4c2f78df3d113 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 4:44 a.m.