Triple

T4756238
Position Surface form Disambiguated ID Type / Status
Subject Moscow–Saint Petersburg railway E105594 entity
Predicate servedByTrainService P14525 FINISHED
Object Sapsan E101288 NE FINISHED

How this triple was built (3 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: Sapsan | Statement: [Moscow–Saint Petersburg railway, servedByTrainService, Sapsan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sapsan
Context triple: [Moscow–Saint Petersburg railway, servedByTrainService, Sapsan]
  • A. Sapsan chosen
    Sapsan is a high-speed passenger train service in Russia operated by Russian Railways, primarily running between Moscow and St. Petersburg.
  • B. Tsalka
    Tsalka is a town in southern Georgia known for its ethnically diverse population and its location near the Tsalka Reservoir in the Kvemo Kartli region.
  • C. Trasianka
    Trasianka is a mixed East Slavic speech variety, primarily combining elements of Belarusian and Russian, commonly used in informal communication in Belarus.
  • D. Mutayr
    Mutayr is a prominent Arabian tribal confederation historically rooted in the Najd region of central Arabia.
  • E. Aegitna
    Aegitna is the ancient name of the city now known as Cannes on the French Riviera.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: servedByTrainService
Context triple: [Moscow–Saint Petersburg railway, servedByTrainService, Sapsan]
  • A. servedByRailroad
    Indicates that a location or facility is provided with transportation or service by a railroad line or company.
  • B. railwayTypeServed
    Indicates the type of railway system or service that a given entity (such as a station, line, or facility) is designed to serve or accommodate.
  • C. transportationServedBy chosen
    Indicates that a transportation facility, route, or area is provided service or coverage by a specific transportation provider or mode.
  • D. railServiceType
    Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
  • E. usesTrainNumber
    Indicates that one entity operates, identifies, or references another entity by a specific train number.
  • F. None of above.

Provenance (4 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_69bd43f14cac819081c7c69803648211 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64e9d80c819088532921a46ea1d6 completed March 20, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a6c7f3c8190b97705bd859c82e8 completed March 21, 2026, 6:27 a.m.
PD Predicate disambiguation batch_69bd6223defc8190823665a6592c1154 completed March 20, 2026, 3:05 p.m.
Created at: March 20, 2026, 1:20 p.m.