Triple

T21638178
Position Surface form Disambiguated ID Type / Status
Subject Thomas and the Magic Railroad E534014 entity
Predicate hasHumanCharacter P12208 FINISHED
Object Patch NE NERFINISHED

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: Patch | Statement: [Thomas and the Magic Railroad, hasHumanCharacter, Patch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patch
Context triple: [Thomas and the Magic Railroad, hasHumanCharacter, Patch]
  • A. Patch
    Patch is a surname most notably associated with Alexander Patch, a senior U.S. Army general who played a key role in World War II operations in Europe.
  • B. Patch chosen
    Patch is one of the Dalmatian puppies from Disney's "101 Dalmatians," recognizable by his distinctive black ear and energetic, adventurous personality.
  • C. Patching
    Patching is a small rural village and civil parish in West Sussex, England, situated within the South Downs and known for its scenic countryside and historic church.
  • D. Patches
    "Patches" is a soul ballad popularized by Clarence Carter in 1970, known for its emotional storytelling about poverty and family responsibility.
  • E. Fix
    Fix is a surname most notably associated with American character actor Paul Fix, known for his extensive work in Western films and television.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c465ae7481908577b7209fdb2a77 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef538eef0481908f5bf0e27f8e054d completed April 27, 2026, 12:16 p.m.
Created at: April 16, 2026, 6:35 p.m.