Triple
T21437822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheinfelden (Baden) |
E528859
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Herten |
—
|
NE NERFINISHED |
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: Herten | Statement: [Rheinfelden (Baden), hasSubdivision, Herten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herten Context triple: [Rheinfelden (Baden), hasSubdivision, Herten]
-
A.
Herten
chosen
Herten is a town in the Ruhr area of North Rhine-Westphalia, western Germany, historically shaped by coal mining and now known for its transition to renewable energy and green urban development.
-
B.
Hundested
Hundested is a small coastal town in North Zealand, Denmark, known for its harbor, beaches, and maritime activities.
-
C.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
D.
Hedensted
Hedensted is a town and municipality in the Central Denmark Region known for its residential communities and local industry.
-
E.
Glostrup
Glostrup is a suburban town and municipality in the Copenhagen metropolitan area of Denmark, known for its residential neighborhoods and commercial districts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b53972e48190bc8bbc543173854c |
completed | April 22, 2026, 11:47 a.m. |
Created at: April 16, 2026, 6:03 p.m.