Triple

T15216230
Position Surface form Disambiguated ID Type / Status
Subject Murmansk Railway E363642 entity
Predicate terminus P388 FINISHED
Object Petrozavodsk E101419 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: Petrozavodsk | Statement: [Murmansk Railway, terminus, Petrozavodsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Petrozavodsk
Context triple: [Murmansk Railway, terminus, Petrozavodsk]
  • A. Petrozavodsk, Russia chosen
    Petrozavodsk is the capital city of Russia’s Republic of Karelia, located on the western shore of Lake Onega and known as a regional cultural and industrial center.
  • B. Pskov
    Pskov is an ancient Russian city near the Estonian border, known for its medieval kremlin, historic churches, and role as a key fortress in northwestern Russia.
  • C. Kalyazin
    Kalyazin is a historic town in Tver Oblast, Russia, known for its partially submerged bell tower in the Uglich Reservoir.
  • D. Vesyegonsk
    Vesyegonsk is a small town in Tver Oblast, Russia, situated on the shores of the Rybinsk Reservoir and known historically as a local administrative and trading center.
  • E. Muroran
    Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a63464c8190afab59257c6a2095 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:11 a.m.