Triple

T2643588
Position Surface form Disambiguated ID Type / Status
Subject The Wind in the Willows (1983 British stop-motion animated film) E62933 entity
Predicate featuresCharacter P626 FINISHED
Object Badger E285185 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: Badger | Statement: [The Wind in the Willows (1983 British stop-motion animated film), featuresCharacter, Badger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Badger
Context triple: [The Wind in the Willows (1983 British stop-motion animated film), featuresCharacter, Badger]
  • A. Badger chosen
    Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
  • B. Badger
    Badger is a fictional character appearing in the work "The Return of Ulysses."
  • C. Badgers
    Badgers is the nickname for the athletic teams representing the University of Wisconsin–Madison in collegiate sports.
  • D. Porcupine
    Porcupine is a historic mining community and neighborhood within the city of Timmins in northeastern Ontario, Canada.
  • E. Wolf
    Wolf is a song by American singer Miguel from his album "War & Leisure."
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd90046dc81908bab3440733f1e98 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d3d6a54819090068ef1807ca921 completed March 10, 2026, 1:31 p.m.
Created at: March 6, 2026, 9:53 p.m.