Triple

T3677473
Position Surface form Disambiguated ID Type / Status
Subject Bug River E78028 entity
Predicate passesNear P416 FINISHED
Object Brest 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 | Statement: [Bug River, passesNear, Brest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brest
Context triple: [Bug River, passesNear, Brest]
  • A. Brest
    Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
  • B. 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.
  • C. Pinsk
    Pinsk is a historic city in southwestern Belarus, known for its location on the Pina River and its rich cultural and architectural heritage.
  • D. Vilna
    Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of the region.
  • E. Białystok
    Białystok is a city in northeastern Poland best known as the birthplace of L. L. Zamenhof and the cradle of the international language Esperanto.
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4643cf08190b2d10ddf4aac7407 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48859949081908fd8291bf6a3372b completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:25 p.m.