Triple

T11207248
Position Surface form Disambiguated ID Type / Status
Subject Lipetsk Oblast E265202 entity
Predicate hasBorderWith P224 FINISHED
Object Ryazan Oblast E107829 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: Ryazan Oblast | Statement: [Lipetsk Oblast, hasBorderWith, Ryazan Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryazan Oblast
Context triple: [Lipetsk Oblast, hasBorderWith, Ryazan Oblast]
  • A. Ryazan Oblast chosen
    Ryazan Oblast is a federal subject of central Russia known for its historic cities, agricultural landscapes, and location along the Oka River southeast of Moscow.
  • B. Oryol Oblast
    Oryol Oblast is a federal subject of western Russia known for its historic role as a major World War II battleground and its agricultural and industrial economy centered around the city of Oryol.
  • C. Moscow Oblast
    Moscow Oblast is a federal subject of Russia that surrounds, but does not include, the city of Moscow and serves as a major industrial and population center in western Russia.
  • D. Tambov Oblast
    Tambov Oblast is a federal subject of central Russia known for its fertile agricultural lands and location along the middle reaches of the Don River.
  • E. Voronezh Oblast
    Voronezh Oblast is a federal subject of Russia in the country’s southwest, known for its administrative center Voronezh and its role as an important agricultural and industrial 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8d4eef88190a7f05bca82d919b9 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084a4c2cc81908c8acd3a1123208a completed May 10, 2026, 1:14 p.m.
Created at: April 8, 2026, 9:30 p.m.