Triple
T22442171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa Origliasso |
E554778
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | 4ever |
—
|
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: 4ever | Statement: [Lisa Origliasso, notableWork, 4ever]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 4ever Context triple: [Lisa Origliasso, notableWork, 4ever]
-
A.
4ever
chosen
"4ever" is a pop-rock single by Australian duo The Veronicas that became one of their breakout hits and fan favorites.
-
B.
See Forever
See Forever is the promotional slogan used by One World Observatory to evoke its expansive, panoramic views over New York City and beyond.
-
C.
Forever
Forever is a song that forms part of the musical work or album titled "Daydream."
-
D.
Forever
Forever is a music album best known for featuring the track "Feeling Inside."
-
E.
Forever
Forever is a darkly comedic television series blending surreal elements with relationship drama, best known for starring Maya Rudolph and Fred Armisen as a married couple navigating an unexpected afterlife.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae2f7608190b1c1e8bd12ca2162 |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.