Triple
T28701555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3JS |
E729563
|
entity |
| Predicate | hasEthnicScene |
P173384
|
FINISHED |
| Object | Volendam music tradition |
—
|
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: Volendam music tradition | Statement: [3JS, hasEthnicScene, Volendam music tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnicScene Context triple: [3JS, hasEthnicScene, Volendam music tradition]
-
A.
hasEthnicScope
Indicates that something is relevant or applicable specifically to a particular ethnic group or ethnic context.
-
B.
hasEthnicTarget
Indicates that an action, statement, or event is directed toward or targets a specific ethnic group.
-
C.
hasEthnicCharacteristic
Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
-
D.
hasEthnicMedia
Indicates that there exists media (e.g., newspapers, TV, radio, online outlets) specifically serving or representing a particular ethnic group in relation to the subject.
-
E.
hasEthnicInfluence
Indicates that one entity has a cultural, traditional, or ethnic impact on, or contributes to shaping the ethnic character 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_69f043e6e9688190b6bdd6e5665498ff |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6b56ed31481908c3e5d749e46bad9 |
completed | May 3, 2026, 2:39 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b49339048190b617a6749f648825 |
completed | May 3, 2026, 2:36 a.m. |
Created at: April 28, 2026, 5:42 a.m.