Triple
T20178780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ¡Dos! |
E492669
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Makeout Party |
—
|
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: Makeout Party | Statement: [¡Dos!, hasTrack, Makeout Party]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makeout Party Context triple: [¡Dos!, hasTrack, Makeout Party]
-
A.
Makeout Party
chosen
Makeout Party is a song by the American punk rock band Green Day from their album ¡Dos!.
-
B.
Slumber Party
"Slumber Party" is a pop song by American singer Britney Spears featuring Tinashe, known for its sultry, midtempo vibe and sleepover-themed music video.
-
C.
The Party Crashers
The Party Crashers is a 1958 American teen drama film about rebellious suburban youth, featuring an early performance by actress Frances Farmer.
-
D.
What Happens at the Party
"What Happens at the Party" is a dance-pop/party track by LMFAO from their debut album "Party Rock," known for its energetic beats and party-themed lyrics.
-
E.
After Party
"After Party" is a popular trap-influenced hip-hop song by American rapper Don Toliver, known for its catchy hook and heavy presence on social media and streaming platforms.
- 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.