Triple

T7408232
Position Surface form Disambiguated ID Type / Status
Subject Toonerville Folks E170933 entity
Predicate workOf P4 FINISHED
Object Fontaine Fox E661515 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: Fontaine Fox | Statement: [Toonerville Folks, workOf, Fontaine Fox]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fontaine Fox
Context triple: [Toonerville Folks, workOf, Fontaine Fox]
  • A. Fontaine Fox chosen
    Fontaine Fox was an American cartoonist best known for creating the popular early 20th-century comic strip "Toonerville Folks," which inspired various film adaptations and characters.
  • B. Vachon
    Vachon is a French-origin surname borne by various notable individuals, including artists, athletes, and public figures.
  • C. Freuchie
    Freuchie is a small village in the Kingdom of Fife, Scotland, known for its rural character and historic cricket club.
  • D. Zibelle
    Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
  • E. Virginia Fox
    Virginia Fox was an American silent film actress who appeared in numerous comedies in the 1910s and 1920s and later became known for her long marriage to film producer Darryl F. Zanuck.
  • 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_69c68a6010108190925e5284de022660 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f29acf588190a7c4056bdc4f3ffc completed March 27, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c82775d1188190bcf158da5a02b6e0 completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 3:10 p.m.