Triple

T10115407
Position Surface form Disambiguated ID Type / Status
Subject Tom Swift series E218343 entity
Predicate mainCharacter P1183 FINISHED
Object Tom Swift E682987 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: Tom Swift | Statement: [Tom Swift series, mainCharacter, Tom Swift]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Swift
Context triple: [Tom Swift series, mainCharacter, Tom Swift]
  • A. Tom Swift chosen
    Tom Swift is the adventurous teenage inventor and protagonist of a long-running series of American science fiction and adventure novels for young readers.
  • B. Tom Swift series
    The Tom Swift series is a long-running collection of juvenile science fiction and adventure novels featuring a young inventor hero whose gadget-filled exploits helped popularize technological optimism in early 20th-century American literature.
  • C. Lewis Swift
    Lewis Swift was a 19th-century American astronomer known for his discovery of numerous comets and deep-sky objects.
  • D. Thomas Tinker
    Thomas Tinker was an English Separatist and early Pilgrim who sailed on the Mayflower and died during the first harsh winter at Plymouth Colony.
  • E. Frank Swift
    Frank Swift was an English professional football goalkeeper best known for his long and successful career with Manchester City and for representing England before his death in the 1958 Munich air disaster.
  • 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_69ca83da93fc8190b54e44bc2b34857c completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd161831c81908bb3c77caa7c3ce1 completed April 2, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc2b00488190acca51a797beed45 completed April 5, 2026, 8:55 p.m.
Created at: March 30, 2026, 9:04 p.m.