Triple

T19173454
Position Surface form Disambiguated ID Type / Status
Subject Saint Petersburg Moskovsky railway station E469382 entity
Predicate connectsWith P37 FINISHED
Object Orel E207325 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: Orel | Statement: [Saint Petersburg Moskovsky railway station, connectsWith, Orel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orel
Context triple: [Saint Petersburg Moskovsky railway station, connectsWith, Orel]
  • A. Orel chosen
    Orel is a male given name most famously associated with former Major League Baseball pitcher Orel Hershiser.
  • B. Stritch
    Stritch is a surname most notably associated with American Cardinal Samuel Stritch, a prominent 20th-century Catholic church leader.
  • C. Ostan
    Ostan was a historic city that served as the political and administrative center of the medieval Armenian region of Vaspurakan.
  • D. Ngawi
    Ngawi is a regency capital and regional town in East Java, Indonesia, known as a transportation hub and gateway between Central and East Java.
  • E. Nišville
    Nišville is an international jazz festival held annually in Niš, Serbia, known for showcasing a wide range of jazz and world music performances.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f16613dc8190987c2d79dc616e40 completed April 20, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a06f8ae89dc819098830e25b3552dee completed May 15, 2026, 10:42 a.m.
Created at: April 10, 2026, 12:06 p.m.