Triple
T13930944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big TC |
E334987
|
entity |
| Predicate | influencesSubjectMatterOf |
P98046
|
FINISHED |
| Object | Ty Dolla Sign’s music |
—
|
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: Ty Dolla Sign’s music | Statement: [Big TC, influencesSubjectMatterOf, Ty Dolla Sign’s music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesSubjectMatterOf Context triple: [Big TC, influencesSubjectMatterOf, Ty Dolla Sign’s music]
-
A.
hasInfluenceOnDiscipline
Indicates that one entity exerts an effect, shaping force, or contributing impact on the development, direction, or state of a particular discipline.
-
B.
hasBeenSubjectOf
Indicates that an entity has previously been the focus or target of a particular action, process, or investigation.
-
C.
influencedScholar
Indicates that one scholar has had a significant intellectual or academic impact on another scholar’s work, ideas, or development.
-
D.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
E.
influencesFocus
chosen
Indicates that one entity affects or shapes the attention, concentration, or focal priorities of another entity.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf13b2881908a48058a719d3745 |
completed | April 14, 2026, 12:02 p.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.