Triple

T20863547
Position Surface form Disambiguated ID Type / Status
Subject Susan Peters E513685 entity
Predicate appearedIn P795 FINISHED
Object Song of Russia NE NERFINISHED

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: Song of Russia | Statement: [Susan Peters, appearedIn, Song of Russia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Song of Russia
Context triple: [Susan Peters, appearedIn, Song of Russia]
  • A. Song of Russia chosen
    Song of Russia is a 1944 American romantic musical drama film set in the Soviet Union during World War II, produced by MGM as a piece of wartime pro-Soviet propaganda.
  • B. Nevsky Express
    Nevsky Express is a high-speed Russian passenger train service that operates between Moscow and Saint Petersburg.
  • C. Volga-Volga
    Volga-Volga is a 1938 Soviet musical comedy film, directed by Grigori Aleksandrov and starring Lyubov Orlova, celebrated for its humorous portrayal of amateur musicians traveling to a Moscow competition.
  • D. Our Song
    "Our Song" is a track by the English progressive rock band Yes, featured on their 1983 album "90125."
  • E. Our Song
    "Our Song" is a breakout country single by Taylor Swift that she wrote in high school, known for its catchy storytelling about young love and everyday moments.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f5b01081909452f654d2fc3f50 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c45d2ec4819098abbb901b9fcd87 completed April 21, 2026, 12:27 a.m.
Created at: April 16, 2026, 12:44 p.m.