Triple
T5136145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Words I Might Have Ate |
E115823
|
entity |
| Predicate | musicalArtistStyle |
P33180
|
FINISHED |
| Object | early Green Day sound |
—
|
LITERAL 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: early Green Day sound | Statement: [Words I Might Have Ate, musicalArtistStyle, early Green Day sound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicalArtistStyle Context triple: [Words I Might Have Ate, musicalArtistStyle, early Green Day sound]
-
A.
styleOfMusic
chosen
Indicates the musical genre or stylistic category that characterizes a piece of music, artist, or performance.
-
B.
hasMusicalStyleCharacteristic
Indicates that something possesses or exhibits a particular musical style as a defining characteristic.
-
C.
includesMusicalStyle
Indicates that one entity encompasses, features, or incorporates a particular musical style as part of its content or character.
-
D.
hasSongStyle
Indicates that an entity possesses, is characterized by, or is associated with a particular style or genre of song.
-
E.
hasMusicalArtistType
Indicates that an entity has a specific role or classification as a type of musical artist (e.g., solo artist, band, composer).
- F. None of above.
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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.