Triple
T23006719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muppets Most Wanted |
E572789
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Beaker |
—
|
NE NERFINISHED |
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: [Muppets Most Wanted, hasCharacter, Beaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaker Context triple: [Muppets Most Wanted, hasCharacter, 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.
Tumbler
Tumbler was a series of early 1950s U.S. nuclear weapons tests conducted at the Nevada Test Site to study blast and radiation effects.
-
C.
Tumbler
Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
-
D.
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.
-
E.
Becher
Becher is a German surname most notably associated with Johannes R. Becher, a 20th-century poet and politician who became East Germany’s culture minister.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1835706dc8190b3f9743c0f336bb2 |
completed | April 29, 2026, 4:04 a.m. |
Created at: April 17, 2026, 3:51 p.m.