by transcript | by glosses | by right neighbours | by left neighbours
1428225 | 46-60f
We lived in a quite remote village called Mausbach.
R
UNDER1B^* RIVER1^* $GEST-OFF1^* $INDEX1* $GEST-OFF1^*
L
VILLAGE3*
M
mausbach
1179224 | 31-45f
It was my son who explained to me that the well isn’t right there, but a bit further away.
R
TO-EXPLAIN1* TO-SAY1 $INDEX1 RIVER1^* CLOSE-BY1A AREA1B NO1A
L
M
erklär sagt quelle [MG] bismarck
1183203 | 61+f
One could observe that he was processing everything while playing.
R
TO-SEE1^ $INDEX1* TO-PLAY2 RIVER1^* TO-KNOW-STH2B^ ROUND-EYE1^* TO-KNOW-STH2B^*
L
M
spiel
1584545 | 31-45f
I think they have a stream called Mulde there or Muldental or Pethauer Teich.
R
RIVER1^ $ALPHA1:M-U-L-D-E OR6B* $ALPHA1:M
L
M
mulde oder muldetal
1413703 | 46-60m
At the beach? No, just on the street on the right side.
R
CLOSE-BY1^* RIVER1^ NO1A STREET1B STORE1*
L
M
am strand straße geschäft
1245820 | 31-45m
Well, in the Rhein-Neckar area [northwest Germany] near the cities Mannheim, Heidelberg, Ludwigshafen and Karlsruhe.
R
$ALPHA1:N RIVER1^ ROOM1B* TO-BE-CALLED4*
L
$NUM-ONE-TO-TEN1A:1d
M
neckarraum heißt
1433543 | 18-30m
Right, there are so many curves.
R
YES2 RIVER1^ YES1A
L
M
stimmt kurve
1205568 | 31-45m
Is that the sign?
R
TO-SIGN1A RIVER1^
L
M
2935384-… | 31-45m
I started collecting cars, and always showed her which ones I wanted to get.
R
TO-COLLECT3 CAR1 RIVER1^ TO-LET-KNOW1A* $INDEX1*
L
M
sammeln auto will will
1182062 | 46-60f
Near the Hamburg harbor.
R
HAMBURG2* CLOSE-BY1B RIVER1^ CLOSE-BY1B
L
M
hamburg hafen hafen
1248625-… | 31-45f
You know that they have these parades in North Rhine-Westphalia, in Mainz, Cologne, and so on.
R
TO-KNOW-STH2A NORTH-RHINE-WESTPHALIA1 MOST1B RIVER1^ $GEST-OFF1^* COLOGNE4B* AND-SO-ON2*
L
$INDEX1
M
du nord{rhein}-westfalen meist{ens} mainz köln
1584545 | 31-45f
I think they have a stream called Mulde there or Muldental or Pethauer Teich.
R
$ALPHA1:M-U-L-D-E OR6B* $ALPHA1:M RIVER1^ OR4A* $ALPHA1:P* $GEST-OFF1^
L
M
mulde oder muldetal mulde oder pe{thauer teich}
1430328 | 31-45f
Then there was another poll and the Ruhr region won.
R
MAIN1A^ $INDEX1 $ALPHA1:R RIVER1^
L
M
ruhr
1413251 | 46-60m
Bad Kreuznach is to have a university.
R
$INDEX1 $ALPHA1:K $INDEX1 RIVER1^ $INDEX1 TO-COME1 UNIVERSITY1
L
M
bad kreuznach komm uni
1430328 | 31-45f
There are meadows and a forest. You can use the bridge to cross the river. That's where I went for a walk.
R
MEADOW1A FOREST2A* $PROD RIVER1^ BRIDGE1A TO-GO-FOR-A-WALK1* MOST1A*
L
M
wiese wald wasser brücke spazieren meist
1432043 | 46-60m
You know Kappeln, going along the Schlei river from Schleswig.
R
SCHLESWIG1* $PROD FROM8* RIVER1^ FROM-TO3*
L
M
schleswig kappeln aus schlei
1205568 | 61+m
Yes, because of the three rivers, Danube, Günz and Nau.
R
$LIST1:2of2d GÜNZBURG1* $LIST1:3of3d RIVER1^* $ALPHA1:N-A-U*
L
M
donau günz nau
1430328 | 31-45f
And towards the Rhine where it was really windy.
R
CLOSE-BY1A* WATER1* $PROD $INDEX1 INTEREST1B
L
RIVER1^
M
nah wasser [MG]
1250061-… | 18-30f
There had been a meeting point for the firefighters next to 'Ground Zero’.
R
MAIN1A^ $ALPHA1:W-T-C* PIPE2B^* NEXT-TO1A*
L
NEXT-TO1A* RIVER1^
M
[MG] neben straße w-t-c neben
1429737 | 61+f
I teach in Aachen, Erftstadt, Düren and sometimes in Cologne.
R
ALWAYS4A*
L
AACHEN2 $INDEX1 RIVER1^ $INDEX1 $NAME* $INDEX1
M
immer aachen erftstadt düren
1433543 | 31-45m
Everyone loves the Alps and goes on trips to the mountains.
R
MOUNTAIN1A
L
ALL1A* TO-LOVE-STH1 RIVER1^
M
alle [MG] berg [MG]
1182062 | 46-60f
Ah okay, near the harbor.
R
$ORAL^
L
RIVER1^*
M
am hafen
Mouth: bach
Translational equivalent: brook
by transcript | by glosses | by right neighbours | by left neighbours
1211515 | 61+m
Back in the days, there was a meadow close by the creek, one for cows and another for sheep, and you could also swim across the Rhine.
R
PAST-OR-BACK-THEN1 BROOK1* PLANE3B^* $LIST1:2of2d COW1*
L
M
früher bach weide kuhweide»
1433543 | 18-30m
In the English garden, one can go surfing in the Eisbach [lit.: ice brook; man-made river]. That’s really famous.
R
$INDEX1 WELL-KNOWN1A ICE8 BROOK1* $INDEX1
L
M
surfen bekannt eisbach
1432043 | 46-60m
The woods, sea, hills, streams.
R
FOREST3A OCEAN1A* $PROD BROOK1
L
M
wa{ld} am meer bach
1204877 | 46-60m
Sometimes on the weekends I went swimming in the stream with my brother.
R
TO-GO-THERE1* BROTHER1A* PRESENT-OR-HERE1 BROOK1* TO-SWIM1*
L
M
wochenende bruder da bach schwimmen
1433543 | 31-45m
Yes, one can surf in the Eisbach.
R
$INDEX1 HORSE5^*
L
YES1A ICE8 BROOK1* WAVE1
M
eisbach wellenreiten
Mouth: elbe
Translational equivalent: Elbe
by transcript | by glosses | by right neighbours | by left neighbours
1177054 | 31-45f
The Elbe has also tilted sides, doesn’t it?
R
ELBE-RIVER1* $INDEX1* $PROD $PROD
L
M
elbe [MG]
1178133 | 46-60f
The water kept rising along the course of the Elbe.
R
TO-RISE4^* ELBE-RIVER1* TO-RISE4^*
L
M
mehr mehr mehr mehr mehr elbe mehr mehr
1183720-… | 61+m
On the one side there was water - that was the river Elbe.
R
PLANE3B^* $INDEX1* CLOSED7^* ELBE-RIVER1* OFF-OR-TO-REMOVE-STH1B*
L
FLAP1A^* FLAP1A^* FLAP1A^*
M
wasser elbe
1431690 | 46-60m
I don't know what the region around the Elbe looks like.
R
AREA1A* $NUM-ONE-TO-TEN1A:2d LATER1^ ELBE-RIVER1* $GEST-OFF1^* I2 NO-CLUE1
L
M
elbe [MG]
1584545 | 31-45f
The River Elbe in Saxony/
R
ELBE-RIVER1 ACTUALLY1B* ELBE-RIVER1 $ALPHA1:S
L
M
elbe eige{ntlich} elbe sachsen
1432043 | 46-60m
Old/ Along the Elbe-Lübeck-Canal.
R
OLD5A* ELBE-RIVER1 LÜBECK1A CHANNEL1*
L
M
a{lt} elbe lübeck kana{l}
1584545 | 31-45f
Then they also have the Elbe where many of the large steamboats navigate.
R
$GEST-OFF1^ ELBE-RIVER1 $GEST-OFF1^* MORE1 SHIP1
L
M
elbe mehr
1583964 | 31-45f
I worked as a cleaning lady at the restaurant ‘Kornhaus’. It’s right on the banks of the Elbe.
R
RESTAURANT1 WITH2 ELBE-RIVER1 NARROW1A^*
L
$ALPHA1:K-O-R-N-H-A-U-S
M
restaurant kornhaus elbe
1583964 | 31-45f
The “Kornhaus” [restaurant] is situated directly on the banks of the Elbe.
R
$ALPHA1:K-O OUTDOORS1B^ ELBE-RIVER1 $ALPHA1:K-O-R-N-H-A-U-S $INDEX1 $GEST-NM-SHAKE-HEAD1^
L
$INDEX1
M
korn{haus} elbe kornhaus
1584545 | 31-45f
The River Elbe in Saxony/
R
ELBE-RIVER1 ACTUALLY1B* ELBE-RIVER1 $ALPHA1:S
L
M
elbe eige{ntlich} elbe sachsen
1431690 | 31-45m
There was this big flood around the river Elbe in 2002.
R
AIM2^ $INDEX1 $GEST-TO-PONDER1^ ELBE-RIVER1 WAS1* $NUM-THOUSANDS1:2 $NUM-ONE-TO-TEN1B:2*
L
M
elbe war zweitausendzwei
1179224 | 46-60f
Always going straight ahead, until you reach the river Elbe.
R
STRAIGHT-AHEAD1*
L
UNTIL-OR-TO1* $GEST-OFF1^* ELBE-RIVER1
M
bis elbe
1179224 | 46-60f
If the weather is nice, you can have a rest at the Elbe.
R
BEAUTIFUL5 $ORAL^ TO-LIE-LEG1A*
L
ELBE-RIVER1*
M
schönes wetter elbe [MG]
Mouth: fluss
Translational equivalent: river
by transcript | by glosses | by right neighbours | by left neighbours
1419931 | 31-45f
And the Spree, because there are many possible ways to go for a walk along the Spree.
R
RIVER1* WHY2A* RIVER1* MUCH1C*
L
M
spree warum spree viel
1420216 | 18-30m
That was the Elbe. There was once a flood in Magdeburg and Dresden.
R
$ALPHA1:E-L-B-E RIVER1* PAST-OR-BACK-THEN1* THERE1* MAGDEBURG1*
L
M
elbe früher magdeburg
1205568 | 61+m
Yes, because of the three rivers, Danube, Günz and Nau.
R
I1^ RIVER1* $LIST1:1of1d $NUM-ONE-TO-TEN1A:3d
L
BECAUSE1
M
weil drei
1419931 | 31-45f
Ah okay. Yes, it is located at the Spree.
R
$GEST-NM^ RIVER1* RIGHT-OR-AGREED1B
L
M
stimmt
1247800 | 61+m
A path leads to a river and past the riverside on the left.
R
TO-GO2A RIVER1* LEFT1
L
LEFT3
M
[MG] fluss
1290126 | 31-45m
Yes, the Danube is there.
R
$GEST-NM-NOD-HEAD1^ RIVER1*
L
M
fluss
1211515 | 61+m
I was really happy about it because it was close to the city and there were so many possibilities to take a walk, for example along the river Wutach.
R
MOVEMENT1A^* TO-GO1A* RIVER1* RIVER1* PARALLEL1A^*
L
M
spazieren am wutach wutach flu{ss}
1431690 | 46-60m
So we had the flood in Germany and much later, I don't remember when, was another flood in Frankfurt/Oder.
R
TO-BELIEVE2A* OUTDOORS1A^* TO-KNOW-STH2B^ RIVER1* RIVER1 $INDEX1* FRANKFURT1*
L
M
glau{ben} später [MG] frankfurt
1419931 | 31-45f
And the Spree, because there are many possible ways to go for a walk along the Spree.
R
RIVER1* WHY2A* RIVER1* MUCH1C* POSSIBLE1* $INDEX1*
L
M
spree warum spree viel möglichkeit lauf lauf lauf
1184145 | 61+m
The River Main passes three cities: Schweinfurt, Würzburg and Aschaffenburg.
R
$NUM-ONE-TO-TEN1A:3d $CUED-SPEECH:M2 CORNER1* RIVER1* $ALPHA1:SCH LOCATION1A^* LOCATION1A^*
L
M
drei-main-eck [MG] schweinfurt würzburg
1419931 | 31-45f
There is this one house by the Spree, but I don’t know what it is called exactly.
R
$GEST-TO-PONDER1^ TO-BELIEVE2A* HOUSE1A RIVER1* TO-BE-CALLED1A
L
M
[MG] glaube haus am spree wie heißt das
1431690 | 31-45m
It is, but we also have a river down in the valley.
R
MY3 AT-HOME1A MY1* RIVER1* PRESENT-OR-HERE1
L
M
mein fluss da
1210208 | 46-60m
After all, they have three rivers joining which benefits a fast rise of the water.
R
$INDEX1* TO-HAVE-TO-OWN1* $NUM-ONE-TO-TEN1A:3d RIVER1* $PROD $PROD FAST3A*
L
M
weil hat drei flüsse [MG] [MG] schnell»
1179224 | 46-60f
Rainfall helped form some arms of the river that all led to the Alster and filled it.
R
$INDEX1* RAIN2A* THROUGH2A* RIVER1* UNTIL-OR-TO1* $PROD
L
M
wie regen durch fluss bis alster
1181027 | 18-30f
The youth center was near a river.
R
HOME1A $INDEX1 $ORAL^ RIVER1*
L
M
jugendheim an einem fluss
1183720-… | 61+m
Afterwards, we went to the mountains, because there was a river close to Italy. That was fun.
R
MOST1A CLOSE-BY1B* ITALY1* RIVER1* TO-LOOK-AT3* FUN1^
L
M
meist nahe italien fluss [MG]
1420216 | 18-30m
It was a close call for me because my house is only ten kilometers away from the river.
R
DISTANCE-OR-RANGE1* $NUM-ONE-TO-TEN1A:10 KILOMETRE1* RIVER1*
L
M
[MG] zehn kilome{ter} fluss
1211515 | 61+m
I was really happy about it because it was close to the city and there were so many possibilities to take a walk, for example along the river Wutach.
R
MUCH1C* MOVEMENT1A^* TO-GO1A* RIVER1* RIVER1* PARALLEL1A^*
L
M
viel spazieren am wutach wutach flu{ss}
1180339-… | 31-45m
There you can bike along the Weser, wait no, along the Wümme northwards from Bremen-Horn all the way to Ritterhude.
R
$PROD VERY7^* EXHAUSTING5 RIVER1* $ALPHA1:W-U-NN-E $PROD $PROD
L
M
[MG] weser wümme
1184145 | 61+m
If there was a river, so that water could condense, then maybe, but there is none.
R
RIVER1 $INDEX1* RIVER1 MOIST2
L
M
fluss fluss feuchtigkeit»
1290126 | 31-45m
Exactly, the Danube is there.
R
$GEST-NM-NOD-HEAD1^ RIVER1
L
M
fluss
1248400 | 46-60m
It's just that a nuclear power plant always needs to have a river or an ocean close by.
R
MUST1 TO-HAVE-TO-OWN1 CLOSE-BY1B RIVER1 OR1* OCEAN1A
L
M
muss haben nah fluss oder meer
1212218 | 46-60m
(Not really, but a few things in the city, mostly the Nile.)
R
MOST1A $INDEX1 ON-OR-AT1* RIVER1 $INDEX1
L
M
m{eistens} am nil
1179868 | 31-45f
I think it was in 1979/1980 that the water of a river was rising so much that it caused flooding.
R
BETWEEN1B* $INDEX1 SUDDENLY4* RIVER1 HIGH1^* $GEST-TO-PONDER1^* WATER1*
L
M
[MG] fluss hochhaus hochwasser»
1431690 | 46-60m
So we had the flood in Germany and much later, I don't remember when, was another flood in Frankfurt/Oder.
R
OUTDOORS1A^* TO-KNOW-STH2B^ RIVER1* RIVER1 $INDEX1* FRANKFURT1* OR1*
L
M
später [MG] frankfurt oder»
1184145 | 61+m
If there was a river, so that water could condense, then maybe, but there is none.
R
RIVER1 $INDEX1* RIVER1 MOIST2 $PROD NONE3*
L
M
fluss fluss feuchtigkeit
1248400 | 46-60m
In Germany, water from power plants must first be purified before it is discharged into the river.
R
GERMAN1* $INDEX1 NONE1* RIVER1 MUST1A^ WATER7B OFF1B^*
L
M
deutschland fluss wasser
1420216 | 18-30m
That was the Elbe. There was once a flood in Magdeburg and Dresden.
R
MAGDEBURG1* THERE1 DRESDEN1* RIVER1 $ALPHA1:E-L-E FLOODWATERS1
L
M
magdeburg dresden elbe hochwasser
1179224 | 46-60f
Munich also has a river running through the city, but that’s different.
R
$GEST-DECLINE1^ DIFFERENT1*
L
MUNICH1A* RIVER1*
M
münchen fluss was and{ers}
1290126 | 31-45m
They carefully crept through the train, opened the window, climbed through and saw the river right next to them.
R
TO-OPEN-WINDOW1* TO-GO2B*
L
WATER5* RIVER1*
M
[MG] wasser
1179224 | 46-60f
And this is supposed to be the source the Alster comes from.
R
SOURCE1C $ORAL^
L
SOURCE1A RIVER1*
M
erste wasser dann fluss
Mouth: ∅
Translational equivalent: Günzburg
by transcript | by glosses | by right neighbours | by left neighbours
2935384-… | 31-45m
Is it south of Günzburg?
R
GÜNZBURG1 DOWN1 GÜNZBURG1* DOWN1^*
L
$INDEX1
M
günzburg süd günzburg süd
1205568 | 61+m
It’s in Günzburg.
R
$INDEX1* $INDEX1* GÜNZBURG1
L
$INDEX4
M
[MG] günzburg
1205568 | 61+m
I stayed in Günzburg for 18 years, until my retirement.
R
I1 PRECISELY1* GÜNZBURG1 $INDEX1*
L
I1 $INDEX1*
M
[MG] günzburg
2935384-… | 31-45m
You live in Günzburg, don’t you?
R
YOU1 APARTMENT5* AREA1A GÜNZBURG1 YOU1* AREA1A APARTMENT5*
L
M
[MG] wohn günzburg wohnen
2935384-… | 61+m
Günzburg county, that’s where I lived.
R
$GEST-ATTENTION1^ IN1 CIRCLE2* GÜNZBURG1 $INDEX1* I1 PAST1
L
M
[MG] im landkreis günzburg
1205568 | 31-45m
Günzburg?
R
$INDEX1* GÜNZBURG1*
L
M
günzburg
2935384-… | 31-45m
Is it south of Günzburg?
R
GÜNZBURG1 DOWN1 GÜNZBURG1* DOWN1^*
L
$INDEX1
M
günzburg süd günzburg süd
1205568 | 61+m
Yes, because of the three rivers, Danube, Günz and Nau.
R
$LIST1:1of1d DANUBE1* $LIST1:2of2d GÜNZBURG1* $LIST1:3of3d RIVER1^* $ALPHA1:N-A-U*
L
M
donau günz nau
Mouth: main
Translational equivalent: Main (river in Germany)
by transcript | by glosses | by right neighbours | by left neighbours
1184145 | 61+m
The Red Main flows there as well but not in Selb.
R
MAIN1 I1 $GEST-OFF1^* $GEST-OFF1^
L
M
bei roter main selb
1184145 | 61+m
And then the River Main flows into the River Rhine.
R
MAIN1 $PROD
L
M
main rhein
1184145 | 61+m
What about the White and Red Main?
R
$INDEX1 WHITE1B $ALPHA1:M MAIN1 $INDEX1* MOUTH2^* MAIN1
L
M
und auch weiße main rote main
1184145 | 61+m
The White and the Red Main merge together as one river. They become the River Main.
R
$PROD $PROD THEN1A MAIN1
L
M
weißer main roter main [MG] dann main
1184145 | 61+m
What about the White and Red Main?
R
MAIN1 $INDEX1* MOUTH2^* MAIN1
L
M
weiße main rote main
1184145 | 61+m
They have built a wall to control the flood alongside the River Main.
R
TO-GIVE2 TO-BUILD1* WHAT1A* WITH1B HIGH5 PROTECTION1A
L
MAIN1*
M
gibt bauen was main mit hochwasserschutzmauer»
1184145 | 61+m
Everybody comes to Würzburg to take a bath in the Main. Priests, bishops, they all take a bath in the Main, or a shower [laughs].
R
ALL1A* WHAT2* TO-SWEAT1B^* MAIN1* TO-THROW1^* TO-PRAY1B^ TO-PRAY1B^
L
M
alle duschen im main pfarrer bischof
Mouth: neckargemünd
Translational equivalent: Neckargemünd (town in the federal state of Baden-Württemberg)
by transcript | by glosses | by right neighbours | by left neighbours
1200689 | 18-30f
Neckargemünd, that's right.
R
NECKARGEMÜND1 YES1A*
L
M
neckargemünd
1182062 | 46-60f
I moved to Neckargemünd, to the vocational school there, the boarding school.
R
NECKARGEMÜND1 NECKARGEMÜND1 SCHOOL2H* SCHOOL2H*
L
M
neckargemünd neckargemünd berufsschule schule
1200689 | 18-30f
I went to a Hauptschule [school for lower secondary education].
R
PERIOD1B NECKARGEMÜND1 SCHOOL1A* TO-GO-THERE1*
L
M
neckargemünd schule
1414123 | 46-60m
In Neckargemünd close to Heidelberg.
R
TO-SAY1 NECKARGEMÜND1 $ALPHA1:G $CUED-SPEECH^* NEAR1C
L
M
neckargemünd bei
1182062 | 46-60f
I moved to Neckargemünd, to the vocational school there, the boarding school.
R
NECKARGEMÜND1 NECKARGEMÜND1 SCHOOL2H* SCHOOL2H* BOARDING-SCHOOL1B
L
M
neckargemünd neckargemünd berufsschule schule internat
1204191 | 61+m
I went to school in Neckargemünd near Heidelberg.
R
I1* SCHOOL2B HEIDELBERG2* NECKARGEMÜND1 NEAR1C HEIDELBERG2 $$EXTRA-LING-ACT^
L
M
ich schule h{eidelberg} neckargemünd bei heidelberg
1200689 | 18-30f
Through the school in Neckargemünd I got to know sign language. Everyone was signing there, and I adopted it.
R
$GEST-OFF1^* THROUGH2A* $INDEX1* NECKARGEMÜND1* $INDEX1* MORE1* TO-SIGN1A*
L
M
durch neckargemünd mehr
Mouth: rhein
Translational equivalent: Rhine (river)
by transcript | by glosses | by right neighbours | by left neighbours
1246681 | 61+m
One sees the Rhine directly in front, ah, no, the Neckar.
R
RHINE-RIVER1* $GEST-NM-SHAKE-HEAD1^ NECKAR1*
L
M
rhein neckar
1211515 | 61+m
Back in the days, there was a meadow close by the creek, one for cows and another for sheep, and you could also swim across the Rhine.
R
SHEEP-$CANDIDATE-STU63^ AREA1D^* OVER-OR-ABOUT1 RHINE-RIVER1* $GEST-OFF1^
L
M
schafweide über rhein
1211515 | 61+m
Now wait, it was the Rhine.
R
$GEST-NM-SHAKE-HEAD1^ $GEST-DECLINE1^* RHINE-RIVER1* TO-JUMP2^
L
M
[MG] rhein rhein
1430328 | 31-45f
In Düsseldorf the historical part is right next to the Rhine.
R
OLD8B CITY2 ALSO3A* RHINE-RIVER1* CLOSE-BY1B* AREA1A^*
L
M
altstadt auch rhein
1245820 | 31-45m
It's quite different in the Rhein-Neckar/
R
DIFFERENT1* $INDEX1* $GEST^ RHINE-RIVER1 $ALPHA1:N*
L
M
andere [MG] rhein
1431690 | 46-60m
To be more specific in the Old Town, a little off the river Rhine.
R
OLD3 CITY2 $INDEX1* RHINE-RIVER1 NEXT-TO1A*
L
M
altstadt rhein
1430328 | 31-45f
I don't know where it was exactly; there were some meadows and a river, maybe the Rhine.
R
$INDEX1 PARALLEL1A^* OR1* RHINE-RIVER1 APPROXIMATELY1^
L
M
stimmt fluss oder rhein
1246681 | 46-60m
Or especially the Rhine region/
R
L
MAINLY1B* RHINE-RIVER1* TERRITORY1*
M
vor allem rheingebiet
1246681 | 46-60m
And the treasure of the Nibelungs is supposedly sunk in the river Rhine.
R
TO-GIVE1A^*
L
AND5* IN1 RHINE-RIVER1* SHOULD1 $ALPHA1:N-N-N
M
und im rhein soll nibelungenschatz
1246681 | 46-60m
So Friesenheim, Oppau, Oggersheim and Rheingönheim were included.
R
$LIST1:3of3d $NAME $LIST1:4of4d RHINE-RIVER1* AREA1A* TOGETHER7
L
TO-SWALLOW1*
M
oggersheim rheingönheim [MG] verschluckt
