Triple
T18965187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autobahn A46 |
E464015
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Erkrath |
—
|
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: Erkrath | Statement: [Autobahn A46, connectsCity, Erkrath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erkrath Context triple: [Autobahn A46, connectsCity, Erkrath]
-
A.
Erkrath
chosen
Erkrath is a town in the German state of North Rhine-Westphalia, situated near Düsseldorf in the district of Mettmann.
-
B.
Steinhagen
Steinhagen is a municipality in North Rhine-Westphalia, Germany, known for its location near Bielefeld and its traditional grain distilleries.
-
C.
Stolzenhagen
Stolzenhagen is a village and locality within the municipality of Wandlitz in the state of Brandenburg, Germany.
-
D.
Velbert
Velbert is a German city in North Rhine-Westphalia known for its metal and lock manufacturing industry and its location between Düsseldorf, Essen, and Wuppertal.
-
E.
Sprockhövel
Sprockhövel is a small town in North Rhine-Westphalia, Germany, known for its historical coal mining heritage and location in the hilly Ruhr region.
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d5d663948190b496fbd2e69c7f43 |
completed | April 20, 2026, 7:29 a.m. |
Created at: April 10, 2026, noon