Triple
T3705058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K Records |
E80871
|
entity |
| Predicate | associatedWithCityScene |
P19735
|
FINISHED |
| Object | Olympia 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: Olympia music scene | Statement: [K Records, associatedWithCityScene, Olympia music scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCityScene Context triple: [K Records, associatedWithCityScene, Olympia music scene]
-
A.
hasAssociatedCity
Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
-
B.
cityScene
Indicates a scene or setting that takes place within an urban or city environment.
-
C.
cityAssociatedWith
Indicates that there is a notable connection or relationship between a city and another entity, such as relevance, involvement, or contextual association.
-
D.
associatedWithLocality
chosen
Indicates a relationship where something has a connection or relevance to a specific geographic place or locality.
-
E.
linkedCity
Indicates that two entities are associated with each other through a specific city, such as being located in, connected via, or related by that city.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54bbfcc8190bec9c16e3749c3b1 |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.