Triple

T3509705
Position Surface form Disambiguated ID Type / Status
Subject Western France E74164 entity
Predicate hasMajorCity P316 FINISHED
Object Brest E53827 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: [Western France, hasMajorCity, Brest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brest
Context triple: [Western France, hasMajorCity, Brest]
  • A. Brest chosen
    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)
    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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc0e1f0c8190b054d9fba16ce4b3 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373e71ae8819096ea39955c92076a completed March 13, 2026, 2:18 a.m.
Created at: March 8, 2026, 3:18 p.m.