Triple

T15715185
Position Surface form Disambiguated ID Type / Status
Subject M. Emmet Walsh E380942 entity
Predicate notableWork P4 FINISHED
Object Critters E285519 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: Critters | Statement: [M. Emmet Walsh, notableWork, Critters]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Critters
Context triple: [M. Emmet Walsh, notableWork, Critters]
  • A. Kritter
    Kritter is a common crocodilian enemy character from the Donkey Kong video game series, serving as one of the primary foot soldiers of the Kremling Krew.
  • B. Critters Buggin
    Critters Buggin is an experimental jazz-fusion and improvisational rock band known for its eclectic, genre-blending sound and innovative live performances.
  • C. Critter Country
    Critter Country is a themed land at Disneyland known for its rustic woodland setting and attractions featuring animal characters.
  • D. Critters franchise chosen
    The Critters franchise is a series of American horror-comedy films centered on small, carnivorous alien creatures that terrorize humans.
  • E. Zoot
    Zoot is a fictional animal character name commonly used in entertainment and media, often evoking a quirky or playful creature.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f90aea0819082a9e9fe0f7780b0 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff7581302c8190918266f04bcf2231 completed May 9, 2026, 5:57 p.m.
Created at: April 10, 2026, 4:45 a.m.