Triple

T3108142
Position Surface form Disambiguated ID Type / Status
Subject Melvin Jerome Blanc E64883 entity
Predicate voicedCharacter P2000 FINISHED
Object Tweety E56471 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: Tweety | Statement: [Melvin Jerome Blanc, voicedCharacter, Tweety]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tweety
Context triple: [Melvin Jerome Blanc, voicedCharacter, Tweety]
  • A. Tweety chosen
    Tweety is a small, yellow canary from the Looney Tunes cartoons, best known for outsmarting Sylvester the Cat with a deceptively cute demeanor.
  • B. Foghorn Leghorn
    Foghorn Leghorn is a loud, fast-talking, Southern-accented cartoon rooster from the Looney Tunes series known for his comedic antics and catchphrases.
  • C. Daffy
    Daffy is the colloquial nickname given to the British World War II Boulton Paul Defiant turret fighter aircraft.
  • D. Daffy Duck
    Daffy Duck is a classic Looney Tunes cartoon character known for his zany, self-centered antics and comedic rivalry with characters like Bugs Bunny.
  • E. Pepé Le Pew
    Pepé Le Pew is a romantic, overly confident skunk from the Looney Tunes cartoons, best known for his comedic, French-accented pursuit of love.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29eacc88190a19c5ca8e53e3dca completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2038c89248190b880108c82ad35b1 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:04 p.m.