Triple

T8880284
Position Surface form Disambiguated ID Type / Status
Subject Kovel Raion E211391 entity
Predicate hasBorderWith P224 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: [Kovel Raion, hasBorderWith, Belarus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belarus
Context triple: [Kovel Raion, hasBorderWith, 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–Poland
    Belarus–Poland refers to the international border region where Belarus and Poland meet, encompassing shared historical, cultural, and ecological landscapes.
  • D. Belorusskaya
    Belorusskaya is a Moscow Metro station that serves as a key transport hub and interchange point near Belorussky railway terminal.
  • E. Moldova
    Moldova is a landlocked Eastern European country situated between Romania and Ukraine, known for its wine production, agricultural economy, and post-Soviet political landscape.
  • 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_69ca838f9e20819096ab1f236a70381a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc61677c9c8190aa09dc2a05d4cf95 completed April 1, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba1809dc81909776f1268cae9004 completed April 3, 2026, 1:01 p.m.
Created at: March 30, 2026, 6:52 p.m.