Triple
T20611027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oran "Hot Lips" Page |
E506445
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | "Skippy" |
—
|
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: "Skippy" | Statement: [Oran "Hot Lips" Page, notableWork, "Skippy"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: "Skippy" Context triple: [Oran "Hot Lips" Page, notableWork, "Skippy"]
-
A.
Skippy
Skippy is a popular American brand best known for its peanut butter products.
-
B.
Skippy
chosen
Skippy is a 1931 American comedy-drama film, based on a popular comic strip, that earned Jackie Cooper an Academy Award nomination as one of Hollywood’s earliest child stars.
-
C.
The Scamp
The Scamp is a British drama film best known for featuring actor Eddie Byrne in a prominent role.
-
D.
Scribbly
Scribbly is a Golden Age comic strip and later comic book series created by Sheldon Mayer, featuring a young cartoonist and known for its humorous, semi-autobiographical stories.
-
E.
The Kipper Kids
The Kipper Kids were a provocative performance art and comedy duo known for their anarchic, absurdist stage acts in the 1970s and 1980s.
- 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aad6f53481908fb242947dda7028 |
completed | April 20, 2026, 10:38 p.m. |
Created at: April 16, 2026, 11:41 a.m.