Triple
T19533093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XO TOUR Llif3 |
E488701
|
entity |
| Predicate | influencedSubculture |
P136681
|
FINISHED |
| Object | emo rap |
—
|
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: emo rap | Statement: [XO TOUR Llif3, influencedSubculture, emo rap]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedSubculture Context triple: [XO TOUR Llif3, influencedSubculture, emo rap]
-
A.
notableSubculture
Indicates that one entity is a significant or well-recognized subculture within the context or domain of the other entity.
-
B.
influencedTradition
Indicates that one entity has had a shaping or guiding effect on the development, practices, or values of a particular tradition.
-
C.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
D.
influencedFashionTrend
Indicates that one entity caused or contributed to a change or direction in another entity’s fashion style or prevailing clothing trends.
-
E.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
- F. None of above. chosen
Provenance (4 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6364091f4819088b27d0ffdf6010d |
completed | April 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69e514c9c00481909b76bda67957e58b |
completed | April 19, 2026, 5:45 p.m. |
| PDg | Predicate description generation | batch_69e51a23300c8190988552491d9783d7 |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 1:41 p.m.