Triple
T976241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ¡Dos! |
E21058
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Makeout Party
Makeout Party is a song by the American punk rock band Green Day from their album ¡Dos!.
|
E114208
|
NE FINISHED |
How this triple was built (4 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!, hasPart, Makeout Party]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makeout Party Context triple: [¡Dos!, hasPart, Makeout Party]
-
A.
Humpin’ Around
"Humpin’ Around" is a 1992 new jack swing single by American R&B singer Bobby Brown, known for its upbeat groove and chart success.
-
B.
Drunk and Hot Girls
"Drunk and Hot Girls" is a controversial, slow-tempo hip-hop track by Kanye West featuring Mos Def from his 2007 album Graduation.
-
C.
The Big Day
The Big Day is Chance the Rapper’s 2019 debut studio album, a concept project centered on his wedding and adult life that received mixed critical reception.
-
D.
Pleasure Wars
Pleasure Wars is a historical and cultural study by Peter Gay that examines changing Western attitudes toward pleasure, sexuality, and bourgeois life.
-
E.
Midnight Madness
Midnight Madness is a popular late-night program at the Toronto International Film Festival that showcases genre films such as horror, action, and cult cinema.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Makeout Party Triple: [¡Dos!, hasPart, Makeout Party]
Generated description
Makeout Party is a song by the American punk rock band Green Day from their album ¡Dos!.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Makeout Party Target entity description: Makeout Party is a song by the American punk rock band Green Day from their album ¡Dos!.
-
A.
Humpin’ Around
"Humpin’ Around" is a 1992 new jack swing single by American R&B singer Bobby Brown, known for its upbeat groove and chart success.
-
B.
Drunk and Hot Girls
"Drunk and Hot Girls" is a controversial, slow-tempo hip-hop track by Kanye West featuring Mos Def from his 2007 album Graduation.
-
C.
The Big Day
The Big Day is Chance the Rapper’s 2019 debut studio album, a concept project centered on his wedding and adult life that received mixed critical reception.
-
D.
Pleasure Wars
Pleasure Wars is a historical and cultural study by Peter Gay that examines changing Western attitudes toward pleasure, sexuality, and bourgeois life.
-
E.
Midnight Madness
Midnight Madness is a popular late-night program at the Toronto International Film Festival that showcases genre films such as horror, action, and cult cinema.
- F. None of above. chosen
Provenance (5 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b46234c88190b2bfc9cafe59d7f7 |
completed | March 1, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac170e8a008190a40001224f8dae2a |
completed | March 7, 2026, 12:16 p.m. |
| NEDg | Description generation | batch_69ac1787a9ac81908f032cd893d3efe8 |
completed | March 7, 2026, 12:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac1807aa388190ad2910966c9d1b04 |
completed | March 7, 2026, 12:20 p.m. |
Created at: March 1, 2026, 7:40 p.m.