Triple
T5068573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuck Time |
E114204
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Fuck Time |
E114204
|
NE FINISHED |
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: [Fuck Time, hasTitle, Fuck Time]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuck Time Context triple: [Fuck Time, hasTitle, Fuck Time]
-
A.
Fuck Time
chosen
"Fuck Time" is a song by the American rock band Green Day, featured on their album ¡Dos!.
-
B.
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.
-
C.
Smashing Time
Smashing Time is a 1967 British satirical comedy film that parodies Swinging London’s fashion and pop culture scene.
-
D.
A Good Time
A Good Time is a 2019 Afrobeats studio album by Nigerian singer Davido, featuring hit singles and collaborations with several international artists.
-
E.
Killing Time
Killing Time is the autobiographical memoir of philosopher of science Paul Feyerabend, in which he reflects on his life, career, and unorthodox views on science and philosophy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd749dd1a08190858fa739df024eb4 |
completed | March 20, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea4a027a88190a515a374e5405d8a |
completed | March 21, 2026, 2:01 p.m. |
Created at: March 20, 2026, 1:39 p.m.