Triple

T8720002
Position Surface form Disambiguated ID Type / Status
Subject TER Bretagne E206986 entity
Predicate connectsCity P4245 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: [TER Bretagne, connectsCity, Brest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brest
Context triple: [TER Bretagne, connectsCity, 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. Lvov
    Lvov is a Russian noble family name most notably borne by Georgy Lvov, the first head of the Russian Provisional Government after the February Revolution of 1917.
  • E. Żory
    Żory is a city in southern Poland known for its historical roots in the Silesian region and its mix of industrial and residential character.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d02a52c81909f93622ae6920b80 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28f599a481908e93bc5b5c41296e completed April 3, 2026, 2:41 a.m.
Created at: March 30, 2026, 6:36 p.m.