Triple
T20348135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Day singles |
E495927
|
entity |
| Predicate | includesWork |
P2011
|
FINISHED |
| Object | Welcome to Paradise |
—
|
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: Welcome to Paradise | Statement: [Green Day singles, includesWork, Welcome to Paradise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Welcome to Paradise Context triple: [Green Day singles, includesWork, Welcome to Paradise]
-
A.
Welcome to Paradise
chosen
"Welcome to Paradise" is a popular punk rock song by Green Day, best known from their breakthrough 1994 album "Dookie."
-
B.
Walk into Paradise
Walk into Paradise is a 1956 Australian–French adventure film starring Chips Rafferty as a patrol officer in Papua New Guinea.
-
C.
Paradise
Paradise is a popular high-elevation area on the south slope of Mount Rainier known for its spectacular wildflower meadows, hiking trails, and panoramic mountain views.
-
D.
Paradise
"Paradise" is a song by the artist Free Spirit, known for its uplifting, melodic rock sound and emotive lyrics.
-
E.
Paradise
"Paradise" is a 1997 novel by Nobel Prize–winning author Toni Morrison that explores race, gender, community, and violence in an all-Black town in Oklahoma.
- 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_69e0b4a3320881909495ae8bc30bc2dc |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67839e7b48190876ce7133a20c65b |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:24 a.m.