Triple

T16984436
Position Surface form Disambiguated ID Type / Status
Subject Brzeg E412025 entity
Predicate twinTown P1072 FINISHED
Object Brest (Belarus) E41676 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: Brest (Belarus) | Statement: [Brzeg, twinTown, Brest (Belarus)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brest (Belarus)
Context triple: [Brzeg, twinTown, Brest (Belarus)]
  • A. Brest (Belarus) chosen
    Brest is a city in southwestern Belarus near the Polish border, known as a major transport hub and for the historic Brest Fortress, a key World War II memorial.
  • B. Brest
    Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
  • C. Minsk
    Minsk is the capital and largest city of Belarus, serving as its political, economic, and cultural center.
  • D. Молодечно
    Молодечно — город в Минской области Беларуси, являющийся важным региональным центром с развитой инфраструктурой и историческим наследием.
  • E. Pinsk
    Pinsk is a historic city in southwestern Belarus, known for its location on the Pina River and its rich cultural and architectural heritage.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d18a0bf881908c449f499eb86495 completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b412dd48190862fde6d1656113d completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 5:32 a.m.