Triple

T13514947
Position Surface form Disambiguated ID Type / Status
Subject Walter Huston E322734 entity
Predicate portrayed P1668 FINISHED
Object Mr. Scratch E672661 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: Mr. Scratch | Statement: [Walter Huston, portrayed, Mr. Scratch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. Scratch
Context triple: [Walter Huston, portrayed, Mr. Scratch]
  • A. Mr. Scratch chosen
    Mr. Scratch is the cunning, devilish antagonist who bargains for souls in Stephen Vincent Benét’s short story "The Devil and Daniel Webster."
  • B. Grubby the Miner
    Grubby the Miner is the pickaxe-wielding, hard-hat-wearing mascot representing the athletic teams and spirit of South Dakota Mines.
  • C. Skully
    Skully is a small, talkative green parrot who serves as a lookout and helpful companion to the young pirate crew in the children's animated series "Jake and the Never Land Pirates."
  • D. Buckwild
    Buckwild is an American hip-hop producer and member of the Diggin' in the Crates Crew (D.I.T.C.), known for his influential work with artists like The Notorious B.I.G., O.C., and Big L.
  • E. Tik-Tok
    Tik-Tok is a mechanical man from L. Frank Baum’s Oz series, often considered one of the earliest robots in modern fantasy literature.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa0ed508190b2855171b1945e84 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75494642881909f33962afe26f427 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:44 p.m.