Triple
T23111217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pink Slip |
E576324
|
entity |
| Predicate | influencedByRealWorldGenre |
P20936
|
FINISHED |
| Object | early 2000s pop punk |
—
|
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 2000s pop punk | Statement: [Pink Slip, influencedByRealWorldGenre, early 2000s pop punk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedByRealWorldGenre Context triple: [Pink Slip, influencedByRealWorldGenre, early 2000s pop punk]
-
A.
influencedByGenre
chosen
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
B.
influencedByRealWorldConcept
Indicates that something is shaped, inspired, or determined by an existing concept, phenomenon, or principle from the real world.
-
C.
influenceOnGenre
Indicates how strongly one entity has shaped, affected, or contributed to the development or characteristics of a particular genre.
-
D.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
E.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
- 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_69e245f4af548190898d434a64a1e774 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e0f4d188190a9395074c630ab0d |
completed | April 29, 2026, 4:50 a.m. |
| PD | Predicate disambiguation | batch_69ef89f020588190b43393e048e7eda3 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:58 p.m.