Triple

T14759370
Position Surface form Disambiguated ID Type / Status
Subject Return to Oz E346814 entity
Predicate featuresCharacter P626 FINISHED
Object Tik-Tok E239330 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: Tik-Tok | Statement: [Return to Oz, featuresCharacter, Tik-Tok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tik-Tok
Context triple: [Return to Oz, featuresCharacter, Tik-Tok]
  • A. Tik-Tok chosen
    Tik-Tok is a mechanical man from L. Frank Baum’s Oz series, often considered one of the earliest robots in modern fantasy literature.
  • B. Totak
    Totak is a lake in Vinje municipality in Vestfold og Telemark county, Norway, known for its scenic mountain surroundings and role in local hydropower.
  • C. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • D. Pogo
    Pogo is a highly intelligent, anthropomorphic chimpanzee who serves as a loyal assistant and father figure to the Hargreeves siblings in *The Umbrella Academy* series.
  • E. Mr. Scratch
    Mr. Scratch is the cunning, devilish antagonist who bargains for souls in Stephen Vincent Benét’s short story "The Devil and Daniel Webster."
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f0f5a48190af008352c26574d7 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cefb7c08190bf69b15165f046d0 completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:30 a.m.