Triple

T4958499
Position Surface form Disambiguated ID Type / Status
Subject Tula E111344 entity
Predicate hasTwinTown P919 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: [Tula, hasTwinTown, Brest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brest
Context triple: [Tula, hasTwinTown, 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. 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. Vilna
    Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of the region.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71d834c0819087f3faafdc9b4228 completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81e4ccc4819090223633fdb04eee completed March 21, 2026, 11:32 a.m.
Created at: March 20, 2026, 1:32 p.m.