Triple
T976435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinhead Gunpowder |
E21062
|
entity |
| Predicate | hasInfluenceFromScene |
P22079
|
FINISHED |
| Object | East Bay punk 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: East Bay punk scene | Statement: [Pinhead Gunpowder, hasInfluenceFromScene, East Bay punk scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluenceFromScene Context triple: [Pinhead Gunpowder, hasInfluenceFromScene, East Bay punk scene]
-
A.
hasSubsequentInfluence
Indicates that one entity has an influence or effect that occurs after, and is causally or temporally downstream from, another entity or event.
-
B.
influencedByCurrent
Indicates that something’s state, behavior, or outcome is affected or determined by the current conditions, context, or situation.
-
C.
capturedIn
Indicates that one entity was taken prisoner, seized, or otherwise brought under control within the context, location, or event represented by another entity.
-
D.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
E.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b46344048190b7a13b8f3ad9f455 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b344f6f48190ba03ce593c94176b |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.