Triple

T7080533
Position Surface form Disambiguated ID Type / Status
Subject M-1 highway E164941 entity
Predicate passesThrough P225 FINISHED
Object Moscow Oblast E13313 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: Moscow Oblast | Statement: [M-1 highway, passesThrough, Moscow Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow Oblast
Context triple: [M-1 highway, passesThrough, Moscow Oblast]
  • A. Moscow Oblast chosen
    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.
  • B. Ryazan Oblast
    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.
  • C. Nizhny Novgorod Oblast
    Nizhny Novgorod Oblast is a federal subject of central Russia known for its major industrial centers, historical cities, and strategic location along the Volga River.
  • D. Kaluga Oblast
    Kaluga Oblast is a federal subject of western Russia known for its historical cities, space industry heritage, and location southwest of Moscow.
  • E. Tver Oblast
    Tver Oblast is a federal subject of western Russia known for its forests, lakes, and historic towns, and for encompassing the headwaters of major rivers including the Volga.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4f063488190b9e1c614a9294bd1 completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9c2dc39fc8190ae244a4077808e17 completed March 30, 2026, 12:25 a.m.
Created at: March 27, 2026, 2:40 p.m.