Triple

T11373279
Position Surface form Disambiguated ID Type / Status
Subject Sandra Dickinson E269396 entity
Predicate performedVoiceIn P55263 FINISHED
Object Balto E798447 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: Balto | Statement: [Sandra Dickinson, performedVoiceIn, Balto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balto
Context triple: [Sandra Dickinson, performedVoiceIn, Balto]
  • A. Balto chosen
    Balto is the famous sled dog who led his team on the final leg of the 1925 serum run to Nome, Alaska, becoming a symbol of bravery and endurance.
  • B. Misha the Bear
    Misha the Bear is the cheerful bear mascot created for the 1980 Moscow Summer Olympics, widely remembered for its role in the Games’ ceremonies and merchandise.
  • C. Brisky the Bear
    Brisky the Bear is the costumed bear mascot of Japan’s Hokkaido Nippon-Ham Fighters professional baseball team, known for entertaining fans at games and team events.
  • D. Boomer the Bear
    Boomer the Bear is the costumed bear mascot who represents Missouri State University at athletic events and campus activities.
  • E. Laika
    Laika is an American stop-motion animation studio renowned for visually distinctive, critically acclaimed films such as Coraline, ParaNorman, and Kubo and the Two Strings.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea8d244c8190b865260338edb532 completed April 9, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58bdaabd48190ab533c1c7f3b5fd8 completed April 20, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:33 p.m.