POWDER1A^

	
	10

≙ POWDER1A^ (3 tokens)
by transcript | by glosses | by right neighbours | by left neighbours
1432043 sh08 | 46-60m    There’s a lot of tourists on the beach.
r				POWDER1A^	BEACH1*	VERY6	TOURIST1*
l
m				strand		[MG]	touri{st} touri{st} touri{st}
1289793 mst02 | 18-30f    There’s also Bad Salzuflen.
r				POWDER1A^	$INDEX1
l
m				bad salzuflen
1289793 mst02 | 18-30f    Bad Salzuflen.
r				POWDER1A^	$INDEX1*	$LIST1:2of2d*
l
m				bad salzuflen
= SALT1A (5 tokens)
	Mouth: salz
	frontal 45° 90° from above
	Translational equivalents: salt; salty or savoury
by transcript | by glosses | by right neighbours | by left neighbours
1290581 mst06 | 18-30m    Due to the air and the salty water/
r		AIR1
l	MEANING1*		ON10^*	SALT1A	OCEAN1A*	$INDEX1	SALT1A
m	bedeutet		mit	salzmeer			salzmeer
1290581 mst06 | 18-30m    Due to the air and the salty water/
r						$GEST^
l	SALT1A	OCEAN1A*	$INDEX1	SALT1A	OCEAN1A*
m	salzmeer			salzmeer		[MG]
1249376 goe10 | 46-60m    It doesn’t matter if it’s salt water or fresh water.
r		WHATEVER3	SWEET1	SALT1A	WHATEVER3
l
m		egal	süß		egal
1249376 goe10 | 46-60m    He said both fresh and salt water works, right?
r	TO-SAY1	SWEET1	OR1*	SALT1A
l	$INDEX1
m	sagt	süß	oder	salz
1584545 lei11 | 18-30f    No, no. We add salt and pepper to the tomato sauce with the milk.
r	NO1B	FEELING3^	FEELING3^*	SALT1A	PEPPER1A*	WITH1A	MILK2B*
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m				salz	pfe{ffer}		milch
= SALZGITTER1 (2 tokens)
	Mouth: salzgitter
	frontal 45° 90° from above
	Translational equivalent: Salzgitter
by transcript | by glosses | by right neighbours | by left neighbours
1249131-… goe09 | 46-60f    I worked in Salzgitter but went to a vocational school for hearing people in Brunswick.
r	MEANING1*	I1	$INDEX1	SALZGITTER1	GRID4A	TO-WORK2	BUT1*
l
m	bedeutet	[MG]		salzgitter		arbeit	aber
1249131-… goe09 | 46-60f    I could have continued that career, but I just couldn’t find a new job in Salzgitter.
r	TO-WORK2	PLACE9	I1	SALZGITTER1	GRID4A	TO-OBTAIN3*	NONE7B*
l
m	arbeitsplatz			salzgitter		bekommen	[MG]
= SAND1A (7 tokens)
	Mouth: sand
	frontal 45° 90° from above
	Translational equivalent: sand
by transcript | by glosses | by right neighbours | by left neighbours
1176407 sh02 | 18-30f    Still, I would try to help filling sand into bags and building a sandbag wall as protection.
r	TO-TRY2	TO-GO-EASY1	TO-HELP1*	SAND1A	TO-THROW1*	$PROD	TO-SLIDE-OR-TO-PUSH2^*
l
m			helfen	sand			schutz
1204877 mue03 | 61+m    We played with sand in the sandpit, or with cars.
r			$GEST-OFF1^	SAND1A	$GEST-OFF1^	SAND1A*	DISTINCT2B*
l
m			[MG]	sand		sand	[MG]
1204877 mue03 | 61+m    We played with sand in the sandpit, or with cars.
r	SAND1A*	DISTINCT2B*	$INDEX1	SAND1A	CRATE-OR-BOX1*	DISTINCT2B	TO-PLAY2*
l
m	sand	[MG]		sand			spielen
1179224 hh08 | 31-45f    You know, #I live in Name1, and right around the corner there are those hills, they are sand hills, do you know what I mean?
r	UNDER1A*	TO-OWN-TO-EXIST1	$PROD	SAND1A*	HILL1*	TO-KNOW-STH2A*
l
m	unter	[MG]	dünen	sand		weiß
1432043 sh08 | 46-60m    We were building a sand castle as the tide set in.
r				SAND1A*	I2*	SAND1A*	MOUNTAIN1B^*
l
m				sand	ich	sandburg
1432043 sh08 | 46-60m    We were building a sand castle as the tide set in.
r		SAND1A*	I2*	SAND1A*	MOUNTAIN1B^*	I2*	$PROD
l
m		sand	ich	sandburg		[MG]	[MG]
1204877 mue03 | 61+m    We played with sand in the sandpit, or with cars.
r	$GEST-OFF1^	SAND1A	$GEST-OFF1^	SAND1A*	DISTINCT2B*	$INDEX1	SAND1A
l
m	[MG]	sand		sand	[MG]		sand
= SEED6A (2 tokens)
	Translational equivalent: seed
by transcript | by glosses | by right neighbours | by left neighbours
1249280-… goe09 | 46-60f    After, I distribute the seeds into the many small holes.
r	THEN1A*	HOLE1B*	TO-PUT-IN4*	SEED6A	TO-PUT-IN4*	TO-SCATTER2A	TO-PUT-IN4*
l
m		loch	[MG]	samen
1249280-… goe09 | 46-60f    Right, first, I have to buy tomato seeds.
r	FIRST1A	I1*	TOMATO2A*	SEED6A*	TO-BUY1A	I1*
l
m	zuerst		tomaten	samen	kaufen
= SUGAR1A (10 tokens)
	Mouth: zucker
	frontal 45° 90° from above
	Translational equivalent: sugar
by transcript | by glosses | by right neighbours | by left neighbours
1418836-… ber07 | 31-45m    You then take the so-called jam sugar.
r	THEN7	NAME1B*	$ALPHA1:G_2-E-L-I-R	SUGAR1A	TO-STIR6^*
l
m	dann	name	gelier	zucker
1418836-… ber07 | 31-45m    First take the fruit, then dump the sugar into the pot and thoroughly mix it, then let it boil.
r	FIRST1B	$PROD	THEN1C	SUGAR1A	$PROD	TO-STIR1^*	AND2B*
l
m	zuerst	[MG]	dann	zucker		[MG]	und dann
1246329 fra12 | 61+m    You had to put sugar on the windowsill.
r		YOU1*	MUST1	SUGAR1A	$PROD
l
m		du	musst	zucker [MG]
1248625-… goe06 | 31-45f    There is a lot of sugar in Brunswick.
r		BRUNSWICK1*	MUCH1C	SUGAR1A
l
m		braun{schweig}	viel	zucker
1248625-… goe06 | 31-45f    That’s because of the famous Nordzucker [company that produces sugar].
r				SUGAR1A	NORTH1B	SUGAR1A
l
m				zucker	nordzucker
1248625-… goe06 | 31-45f    That’s because of the famous Nordzucker [company that produces sugar].
r		SUGAR1A	NORTH1B	SUGAR1A
l
m		zucker	nordzucker
1248625-… goe06 | 31-45f    That’s because of the famous Nordzucker [company that produces sugar].
r			TO-KNOW-STH-OR-SB1A*	SUGAR1A	NORTH1B	SUGAR1A
l
m				zucker	nordzucker
1248625-… goe06 | 31-45f    That’s because of the famous Nordzucker [company that produces sugar].
r	TO-KNOW-STH-OR-SB1A*	SUGAR1A	NORTH1B	SUGAR1A
l
m		zucker	nordzucker
1248625-… goe06 | 31-45f    They mostly have fields of white sugar beets.
r	PRIMARILY1	AREA1A^*	MUCH1C	SUGAR1A	$PROD	MUCH1C	FIELD4A*
l
m	[MG]	viele		zuckerrübe		viel
1433543 mue07 | 31-45m    You can get cotton candy or candied almonds.
r						OR5*
l				SUGAR1A	$PROD		TONSILS1A*
m				zuckerwatte		oder	mandel
= TO-SCATTER2A (1 token)
	Translational equivalent: to dust
1249280-… goe09 | 46-60f    After, I distribute the seeds into the many small holes.
r	TO-PUT-IN4*	SEED6A	TO-PUT-IN4*	TO-SCATTER2A	TO-PUT-IN4*
l
m	[MG]	samen
= WÜRZBURG1A (9 tokens)
	Mouth: würzburg
	frontal 45° 90° from above
	Translational equivalent: Würzburg
by transcript | by glosses | by right neighbours | by left neighbours
1184145 nue01 | 61+m    On average, about 250,000 to 300,000 people come to visit Würzburg each year.
r				WÜRZBURG1A	$INDEX1*	TO-COME1	YEAR2A
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m				würzburg		kommen	im jahr
1184145 nue01 | 61+m    Every year more than 300,000 tourists come to visit Würzburg.
r	ALWAYS3	YEAR3A*	ALWAYS3	WÜRZBURG1A	$INDEX1*	TO-VISIT-OR-TO-ATTEND1A*	$INDEX1
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m	immer	ein jahr	immer	würzburg		besuchen
1184145 nue01 | 61+m    They have built a wall to control the flood alongside the River Main.
r			ALSO3A*	WÜRZBURG1A	TO-GIVE2	TO-BUILD1*	WHAT1A*
l
m			auch	würzburg	gibt	bauen	was
1184145 nue01 | 61+m    But the one in Würzburg is bad.
r			$INDEX1*	WÜRZBURG1A	BAD5
l
m				würz{burg}	[MG]
1184145 nue01 | 61+m    There is an African Festival in Würzburg every year.
r			AND2A	WÜRZBURG1A	ALSO1A*	EVERYONE1A*	YEAR2A
l
m			und	würzburg	auch	jedes	jahr
1184145 nue01 | 61+m    Especially a lot of Japanese people come to Würzburg and take pictures of everything.
r	JAPAN2	JAPAN1	AIRPLANE2F*	WÜRZBURG1A	THERE1*	TO-VISIT1*	PHOTO1*
l			$INDEX1
m	japaner	japaner	[MG]	würzburg		[MG]	[MG]
1184145 nue01 | 61+m    All the highways, from north, south, west and east, meet in Würzburg.
r		$GEST^	AND2A	WÜRZBURG1A*	MIDDLE2B^	POINT1A	WAY-COURSE1A^*
l
m			und	würzburg	knotenpunkt		autobahn
1184145 nue01 | 61+m    Würzburg has 60 churches.
r				WÜRZBURG1A*	TO-HAVE-TO-OWN1*	$NUM-TENS2A:6d	CHURCH2A
l
m				würzburg	hat	sechzig	kirchen
1184145 nue01 | 61+m    But there isn’t a certain restaurant in Würzburg I have in mind.
r	$INDEX1*	RESTAURANT1	$INDEX1	WÜRZBURG1A*	AREA1A*	I1	NOTHING1A
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m	lokal			würzburg			hab nicht