Triple
T8840796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eurodance |
E210382
|
entity |
| Predicate | hasRegionalScene |
P84945
|
FINISHED |
| Object | German Eurodance 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: German Eurodance scene | Statement: [Eurodance, hasRegionalScene, German Eurodance scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalScene Context triple: [Eurodance, hasRegionalScene, German Eurodance scene]
-
A.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
B.
containsScene
Indicates that one entity (typically a media item or narrative work) includes or features a particular scene as part of its content.
-
C.
hasSubscene
Indicates that a scene is composed of or contains another scene as a subordinate or nested part.
-
D.
hasRegionalPosition
Indicates that one entity holds a specific role, status, or placement within a defined geographic or regional context relative to another entity.
-
E.
hasRegionalRole
Indicates that an entity holds a specific role, function, or responsibility within a defined geographic region.
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6085fe24819095139f18da92d7e7 |
completed | April 1, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69cc5c25b874819084c9ba391703e066 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cff3608819081d2d7e5c16d44b7 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:48 p.m.