Triple

T9568052
Position Surface form Disambiguated ID Type / Status
Subject The Incredible Mr. Limpet E230837 entity
Predicate musicBy P1952 FINISHED
Object Frank Perkins E660469 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: Frank Perkins | Statement: [The Incredible Mr. Limpet, musicBy, Frank Perkins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank Perkins
Context triple: [The Incredible Mr. Limpet, musicBy, Frank Perkins]
  • A. Frank Perkins chosen
    Frank Perkins was an American composer and songwriter known for his popular light orchestral works and film scores in the mid-20th century.
  • B. Walt Dohrn
    Walt Dohrn is an American animator, voice actor, writer, and director best known for his creative leadership on DreamWorks Animation films such as the Trolls franchise.
  • C. Harold Flender
    Harold Flender was an American writer and screenwriter known for his work in film and television, including contributions to socially conscious projects in the mid-20th century.
  • D. Frank Seiberling
    Frank Seiberling was an American industrialist best known for founding the Goodyear Tire & Rubber Company, which became one of the world’s leading tire manufacturers.
  • E. Alvin Marks
    Alvin Marks was an American inventor known for his work on advanced energy technologies and high-efficiency lighting concepts.
  • 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_69ca847f22188190a56e4a97625bef22 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9987cb0c8190af32a1193de54890 completed April 1, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d152b5b40c81909a84e34a944abfd0 completed April 4, 2026, 6:04 p.m.
Created at: March 30, 2026, 8:04 p.m.