Triple
T20178776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ¡Dos! |
E492669
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Fuck Time |
—
|
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: Fuck Time | Statement: [¡Dos!, hasTrack, Fuck Time]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuck Time Context triple: [¡Dos!, hasTrack, Fuck Time]
-
A.
Fuck Time
chosen
"Fuck Time" is a song by the American rock band Green Day, featured on their album ¡Dos!.
-
B.
Bad Time
"Bad Time" is a song by the Australian rock band The Roulettes, recognized as one of their notable tracks.
-
C.
Fire Time
Fire Time is a science fiction novel by Poul Anderson that explores the complex interactions between humans and aliens on a planet periodically devastated by its star’s intense flares.
-
D.
From Time to Time
From Time to Time is a 2009 British fantasy drama film written and directed by Julian Fellowes, blending a World War II–era family mystery with time-travel elements in an English country house.
-
E.
What a Time
"What a Time" is a melancholic pop song by Julia Michaels, featuring Niall Horan, that reflects on the bittersweet memories of a past relationship.
- 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_69e668ed07c8819091bd9ffda237a91c |
completed | April 20, 2026, 5:57 p.m. |
Created at: April 11, 2026, 11:36 p.m.