Triple
T14710115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Muppet Movie |
E345525
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Dr. Teeth |
E579219
|
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: Dr. Teeth | Statement: [The Muppet Movie, featuresCharacter, Dr. Teeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dr. Teeth Context triple: [The Muppet Movie, featuresCharacter, Dr. Teeth]
-
A.
Dr. Teeth
chosen
Dr. Teeth is the flamboyant, gold-toothed bandleader and keyboardist of the Electric Mayhem in the Muppets franchise.
-
B.
Rufus Ruffcut
Rufus Ruffcut is a rugged lumberjack-style racer and one of the cartoon drivers in the classic Hanna-Barbera series "Wacky Races," known for piloting the Buzz Wagon with his beaver sidekick Sawtooth.
-
C.
Muttley
Muttley is a cartoon dog best known as Dick Dastardly’s snickering sidekick in Hanna-Barbera’s slapstick racing and aviation-themed series.
-
D.
Grover
Grover is a masculine given name most famously borne by Grover Cleveland, the 22nd and 24th president of the United States.
-
E.
Grover
Grover is a furry blue Muppet monster from Sesame Street known for his enthusiastic personality, frequent mishaps, and alter ego "Super Grover."
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb9814e0c8190984ac30d276499cc |
completed | April 14, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb845de08190b933d90809cde830 |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.