Triple
T4246962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slint |
E95552
|
entity |
| Predicate | originatedFromScene |
P3654
|
FINISHED |
| Object | Louisville underground music scene |
—
|
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: Louisville underground music scene | Statement: [Slint, originatedFromScene, Louisville underground music scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originatedFromScene Context triple: [Slint, originatedFromScene, Louisville underground music scene]
-
A.
hasInfluenceFromScene
Indicates that something is affected, shaped, or guided by the characteristics or context of a particular scene.
-
B.
partOfScene
Indicates that one entity functions as a component or element within a larger scene or setting involving another entity.
-
C.
capturedFrom
Indicates that one entity has taken possession or control of another entity away from a specified source or previous holder.
-
D.
containsScene
Indicates that one entity (typically a media item or narrative work) includes or features a particular scene as part of its content.
-
E.
hasOriginIn
chosen
Indicates that something begins, arises, or is derived from a specified source, place, or cause.
- 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_69b3453d91548190b4d4ef8fe52aa2ac |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e9b64ac81908dc44eaae6829b50 |
completed | March 12, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69b347f587148190a1830503459939b6 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:05 p.m.