Triple
T16293088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ennepe-Ruhr-Kreis |
E395573
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object | Autobahn A46 |
E464015
|
NE 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: Autobahn A46 | Statement: [Ennepe-Ruhr-Kreis, hasTransportConnection, Autobahn A46]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Autobahn A46 Context triple: [Ennepe-Ruhr-Kreis, hasTransportConnection, Autobahn A46]
-
A.
Autobahn A46
chosen
Autobahn A46 is a German federal motorway in North Rhine-Westphalia that connects several major cities in the Rhine-Ruhr metropolitan region.
-
B.
Autobahn A44
Autobahn A44 is a major German motorway in western Germany that links key cities and transport hubs, including providing direct access to Düsseldorf Airport.
-
C.
Autobahn A43
Autobahn A43 is a German federal motorway in North Rhine-Westphalia that connects the Ruhr area with the Münsterland region.
-
D.
Autobahn A4
Autobahn A4 is a major east–west German motorway that runs across the country, connecting the Dutch border near Aachen to the Polish border near Görlitz.
-
E.
Autobahn A40
Autobahn A40 is a major east–west motorway in western Germany that runs through the Ruhr area and is known for its heavy traffic and congestion.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2aee6881909fd28547f135427c |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002da268b881908f17980c48d44419 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 5:05 a.m.