Triple
T12351530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love, Damini |
E294498
|
entity |
| Predicate | exploresInfluence |
P104608
|
FINISHED |
| Object | global musical influences |
—
|
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: global musical influences | Statement: [Love, Damini, exploresInfluence, global musical influences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exploresInfluence Context triple: [Love, Damini, exploresInfluence, global musical influences]
-
A.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
-
B.
influencesFocus
Indicates that one entity affects or shapes the attention, concentration, or focal priorities of another entity.
-
C.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
D.
influentialFrom
Indicates that one entity has exerted influence on another, contributing to or shaping the latter’s ideas, behavior, or development.
-
E.
influencedScholar
Indicates that one scholar has had a significant intellectual or academic impact on another scholar’s work, ideas, or development.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f8aa33c8190b22b7dff9559b8ed |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ecb5efc819086a3530282278bb1 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93f607a88819089e89fd263ae9937 |
completed | April 10, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:53 p.m.