Triple
T6271415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Muppet Show |
E140542
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Beaker |
E326088
|
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: Beaker | Statement: [The Muppet Show, featuresCharacter, Beaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaker Context triple: [The Muppet Show, featuresCharacter, Beaker]
-
A.
Beaker
chosen
Beaker is a high-strung, squeaky-voiced lab assistant from The Muppets, known for his nervous demeanor and frequent mishaps in scientific experiments.
-
B.
Jug
"Jug" is the widely used nickname for the Republic P-47 Thunderbolt, a rugged and heavily armed American World War II fighter-bomber aircraft.
-
C.
the Teapot
The Teapot is a prominent asterism in the constellation Sagittarius whose stars outline the shape of a traditional teapot in the night sky.
-
D.
Bunsen
Bunsen is a German surname most famously associated with chemist Robert Bunsen, co-developer of the Bunsen burner.
-
E.
Bottle
Bottle is a lightweight Python web framework used for building simple web applications and APIs in a single file.
- 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063bb340c8190ab81b249cefa91ca |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c2446629248190945f0f4f4a103bbd |
completed | March 24, 2026, 7:59 a.m. |
Created at: March 22, 2026, 4:25 p.m.