Triple

T10640366
Position Surface form Disambiguated ID Type / Status
Subject D5 E250703 entity
Predicate rollingStock P1305 FINISHED
Object ES2G Lastochka E101289 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: ES2G Lastochka | Statement: [D5, rollingStock, ES2G Lastochka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ES2G Lastochka
Context triple: [D5, rollingStock, ES2G Lastochka]
  • A. Lastochka chosen
    Lastochka is a modern Russian electric multiple-unit passenger train brand used primarily for high-speed suburban and regional services.
  • B. Eisenring
    Eisenring is one of the central arsonists in Max Frisch’s play "Biedermann und die Brandstifter," embodying manipulative and destructive tendencies beneath a seemingly harmless exterior.
  • C. Mosina
    Mosina is an alternative name for Vurës, a language spoken on the island of Vanua Lava in Vanuatu.
  • D. Elster
    Elster is a river in central Europe, primarily flowing through the German state of Saxony and its surrounding regions.
  • E. Ferno
    Ferno is a small municipality in the Lombardy region of northern Italy, situated in the province of Varese.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfcbe5308190986bba438d19e852 completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96bcd8c0c8190a0fad6a85b5604bb completed April 10, 2026, 9:29 p.m.
Created at: April 8, 2026, 9:04 p.m.