Triple
T20196570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slappy |
E493099
|
entity |
| Predicate | precedes |
P97
|
FINISHED |
| Object | Kerplunk! |
—
|
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: Kerplunk! | Statement: [Slappy, precedes, Kerplunk!]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kerplunk! Context triple: [Slappy, precedes, Kerplunk!]
-
A.
Kerplunk
chosen
Kerplunk is Green Day's 1991 independent punk rock album that helped establish the band's early reputation and paved the way for their mainstream breakthrough.
-
B.
"Kerblam!"
"Kerblam!" is an episode of the British science fiction television series Doctor Who that satirically explores themes of automation, corporate culture, and worker exploitation within a futuristic galaxy-wide delivery company.
-
C.
Kaboom!
Kaboom! is a fast-paced 1981 Atari 2600 action video game in which players catch falling bombs with buckets, widely regarded as one of the console’s classic titles.
-
D.
Kaboom
Kaboom is a 2010 surreal coming-of-age dark comedy film written and directed by Gregg Araki.
-
E.
Kaboings
Kaboings are a type of Kremling enemy from the Donkey Kong video game series, known for their distinctive bouncing movement and dual-headed appearance.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad99d50819090ddb7b546c65321 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.