Triple

T17186201
Position Surface form Disambiguated ID Type / Status
Subject Drums and Guns E417114 entity
Predicate hasTrack P3284 FINISHED
Object Belarus E13665 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: Belarus | Statement: [Drums and Guns, hasTrack, Belarus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belarus
Context triple: [Drums and Guns, hasTrack, Belarus]
  • A. Belarus chosen
    Belarus is an Eastern European country known for its flat landscapes, dense forests, and historical ties to both the Soviet Union and the broader Slavic cultural sphere.
  • B. Belarus–Russia
    Belarus–Russia refers to the shared border area and bilateral relationship between the Republic of Belarus and the Russian Federation, encompassing close political, economic, and cultural ties.
  • C. Belarus and Latvia
    Belarus and Latvia are neighboring Eastern European countries that were selected to jointly host the 2021 IIHF Ice Hockey World Championship.
  • D. Belarus–Poland
    Belarus–Poland refers to the international border region where Belarus and Poland meet, encompassing shared historical, cultural, and ecological landscapes.
  • E. Belorusskaya
    Belorusskaya is a Moscow Metro station that serves as a key transport hub and interchange point near Belorussky railway terminal.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42d962b988190bdbba81ac63c7e6e completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fce16688190976d3760898ca5d8 completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:37 a.m.