POWDER1A^

	
	10

frontal

45°

90°

from above

≙ POWDER1A^ (3 tokens)
by transcript \| by glosses \| by right neighbours \| by left neighbours
1289793 1289793 \| 18-30f There’s also Bad Salzuflen.
R				POWDER1A^	$INDEX1
L
M				bad salzuflen
1289793 1289793 \| 18-30f Bad Salzuflen.
R				POWDER1A^	$INDEX1*	$LIST1:2of2d*
L						$LIST1:2of2d*
M				bad salzuflen
1432043 1432043 \| 46-60m There’s a lot of tourists on the beach.
R				POWDER1A^	BEACH1*	VERY6	TOURIST1*
L					BEACH1*
M				strand		[MG]	touri{st} touri{st} touri{st}
= 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
1249376 1249376 \| 46-60m It doesn’t matter if it’s salt water or fresh water.
R		WHATEVER3	SWEET1	SALT1A	WHATEVER3
L		WHATEVER3			WHATEVER3
M		egal	süß		egal
1249376 1249376 \| 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 1584545 \| 18-30f No, no. We add salt and pepper to the tomato sauce with the milk.
R		FEELING3^	FEELING3^*	SALT1A	PEPPER1A*	WITH1A	MILK2B*
L	NO1B	FEELING3^					MILK2B*
M				salz	pfe{ffer}		milch
1290581 1290581 \| 18-30m Due to the air and the salty water/
R		AIR1
L	MEANING1*	AIR1	ON10^*	SALT1A	OCEAN1A*	$INDEX1	SALT1A
M	bedeutet		mit	salzmeer			salzmeer»
1290581 1290581 \| 18-30m Due to the air and the salty water/
R						$GEST^
L	SALT1A	OCEAN1A*	$INDEX1	SALT1A	OCEAN1A*	$GEST^
M	salzmeer			salzmeer		[MG]
= SALZGITTER1 (2 tokens)
Mouth: salzgitter
frontal 45° 90° from above
Translational equivalent: Salzgitter (city in the federal state of Lower Saxony)
by transcript \| by glosses \| by right neighbours \| by left neighbours
1249131-10284534-10424015 1249131-… \| 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					GRID4A	TO-WORK2
M	bedeutet	[MG]		salzgitter		arbeit	aber
1249131-10284534-10424015 1249131-… \| 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	TO-WORK2	PLACE9			GRID4A
M	arbeitsplatz			salzgitter		bekommen	[MG]
= SEED6A (2 tokens)
Mouth: ∅
frontal 45° 90° from above
Translational equivalent: seed (plants)
by transcript \| by glosses \| by right neighbours \| by left neighbours
1249280-16043122-16070610 1249280-… \| 46-60f Right, first, I have to buy tomato seeds.
R	FIRST1A	I1*	TOMATO2A*	SEED6A*	TO-BUY1A	I1*
L			TOMATO2A*		TO-BUY1A
M	zuerst		tomaten	samen	kaufen
1249280-16043122-16070610 1249280-… \| 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		HOLE1B*
M		loch	[MG]	samen
= SAND1A (7 tokens)
Mouth: sand
frontal 45° 90° from above
Translational equivalent: sand
by transcript \| by glosses \| by right neighbours \| by left neighbours
1204877 1204877 \| 61+m We played with sand in the sandpit, or with cars.
R			$GEST-OFF1^	SAND1A	$GEST-OFF1^	SAND1A*	DISTINCT2B*
L			$GEST-OFF1^		$GEST-OFF1^	SAND1A*	DISTINCT2B*
M			[MG]	sand		sand	[MG]
1176407 1176407 \| 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		TO-GO-EASY1	TO-HELP1*		TO-THROW1*		TO-SLIDE-OR-TO-PUSH2^*
M			helfen	sand			schutz
1204877 1204877 \| 61+m We played with sand in the sandpit, or with cars.
R	SAND1A*	DISTINCT2B*	$INDEX1	SAND1A	CRATE-OR-BOX1*	DISTINCT2B	TO-PLAY2*
L	SAND1A*	DISTINCT2B*			CRATE-OR-BOX1*	DISTINCT2B	TO-PLAY2*
M	sand	[MG]		sand			spielen
1432043 1432043 \| 46-60m We were building a sand castle as the tide set in.
R				SAND1A*	I2*	SAND1A*	MOUNTAIN1B^*
L							MOUNTAIN1B^*
M				sand	ich	sandburg
1432043 1432043 \| 46-60m We were building a sand castle as the tide set in.
R		SAND1A*	I2*	SAND1A*	MOUNTAIN1B^*	I2*	$PROD
L					MOUNTAIN1B^*	I2*	$PROD
M		sand	ich	sandburg		[MG]	[MG]
1179224 1179224 \| 31-45f You know, I live #in Name1, and x there are those hills, they are sand hills, do you know what I mean?
R	$ANONYMISED-$SAM^	TO-OWN-TO-EXIST1	$PROD	SAND1A*	HILL1*	TO-KNOW-STH2A*
L	$ANONYMISED-$SAM^			SAND1A*
M	#name1	[MG]	dünen	sand		weiß
1204877 1204877 \| 61+m We played with sand in the sandpit, or with cars.
R	$GEST-OFF1^	SAND1A	$GEST-OFF1^	SAND1A*	DISTINCT2B*	$INDEX1	SAND1A
L	$GEST-OFF1^		$GEST-OFF1^	SAND1A*	DISTINCT2B*
M	[MG]	sand		sand	[MG]		sand
= TO-SCATTER2A (1 token)
Mouth: ∅
frontal 45° 90° from above
Translational equivalent: to dust
by transcript \| by glosses \| by right neighbours \| by left neighbours
1249280-16043122-16070610 1249280-… \| 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 (city in the federal state of Bavaria)
by transcript \| by glosses \| by right neighbours \| by left neighbours
1184145 1184145 \| 61+m On average, about 250,000 to 300,000 people come to visit Würzburg each year.
R				WÜRZBURG1A	$INDEX1*	TO-COME1	YEAR2A
L
M				würzburg		kommen	im jahr
1184145 1184145 \| 61+m They have built a wall to control the flood alongside the River Main.
R			ALSO3A*	WÜRZBURG1A	TO-GIVE2	TO-BUILD1*	WHAT1A*
L					TO-GIVE2
M			auch	würzburg	gibt	bauen	was
1184145 1184145 \| 61+m But the one in Würzburg is bad.
R			$INDEX1*	WÜRZBURG1A	BAD5
L
M				würz{burg}	[MG]
1184145 1184145 \| 61+m There is an African Festival in Würzburg every year.
R			AND2A	WÜRZBURG1A	ALSO1A*	EVERYONE1A*	YEAR2A
L			AND2A
M			und	würzburg	auch	jedes	jahr
1184145 1184145 \| 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
L						TO-VISIT-OR-TO-ATTEND1A*
M	immer	ein jahr	immer	würzburg		besuchen
1184145 1184145 \| 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		JAPAN1	$INDEX1			TO-VISIT1*	PHOTO1*
M	japaner	japaner	[MG]	würzburg		[MG]	[MG]
1184145 1184145 \| 61+m Würzburg has 60 churches.
R				WÜRZBURG1A*	TO-HAVE-TO-OWN1*	$NUM-TENS2A:6d	CHURCH2A
L						$NUM-TENS2A:6d	CHURCH2A
M				würzburg	hat	sechzig	kirchen
1184145 1184145 \| 61+m All the highways, from north, south, west and east, meet in Würzburg.
R		$GEST^	AND2A	WÜRZBURG1A*	MIDDLE2B^	POINT1A	WAY-COURSE1A^*
L		$GEST^	AND2A	WÜRZBURG1A*	MIDDLE2B^
M			und	würzburg	knotenpunkt		autobahn»
1184145 1184145 \| 61+m But there isn’t a certain restaurant in Würzburg I have in mind.
R	$INDEX1*	RESTAURANT1	$INDEX1	WÜRZBURG1A*	AREA1A*	I1	NOTHING1A
L	$INDEX1*	RESTAURANT1		WÜRZBURG1A*	AREA1A*		NOTHING1A
M	lokal			würzburg			hab nicht»
= SUGAR1A (10 tokens)
Mouth: zucker
frontal 45° 90° from above
Translational equivalent: sugar
by transcript \| by glosses \| by right neighbours \| by left neighbours
1248625-15324720-15465943 1248625-… \| 31-45f That’s because of the famous Nordzucker [company that produces sugar].
R				SUGAR1A	NORTH1B	SUGAR1A	TO-KNOW-STH-OR-SB1A*
L
M				zucker	nordzucker
1246329 1246329 \| 61+m You had to put sugar on the windowsill.
R		YOU1*	MUST1	SUGAR1A	$PROD
L
M		du	musst	zucker [MG]
1248625-15324720-15465943 1248625-… \| 31-45f There is a lot of sugar in Brunswick.
R		BRUNSWICK1*	MUCH1C	SUGAR1A
L
M		braun{schweig}	viel	zucker
1248625-15324720-15465943 1248625-… \| 31-45f That’s because of the famous Nordzucker [company that produces sugar].
R		SUGAR1A	NORTH1B	SUGAR1A	TO-KNOW-STH-OR-SB1A*	SUGAR1A	NORTH1B
L
M		zucker	nordzucker			zucker	nordzucker»
1418836-15524810-15550340 1418836-… \| 31-45m You then take the so-called jam sugar.
R	THEN7	NAME1B*	$ALPHA1:G_2-E-L-I-R	SUGAR1A	TO-STIR6^*
L					TO-STIR6^*
M	dann	name	gelier	zucker
1418836-15524810-15550340 1418836-… \| 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							AND2B*
M	zuerst	[MG]	dann	zucker		[MG]	und dann
1248625-15324720-15465943 1248625-… \| 31-45f That’s because of the famous Nordzucker [company that produces sugar].
R	NORTH1B	SUGAR1A	TO-KNOW-STH-OR-SB1A*	SUGAR1A	NORTH1B	SUGAR1A
L
M	nordzucker			zucker	nordzucker
1248625-15324720-15465943 1248625-… \| 31-45f They mostly have fields of white sugar beets.
R	PRIMARILY1	AREA1A^*	MUCH1C	SUGAR1A	$PROD	MUCH1C	FIELD4A*
L	PRIMARILY1				$PROD
M	[MG]	viele		zuckerrübe		viel
1248625-15324720-15465943 1248625-… \| 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
1433543 1433543 \| 31-45m You can get cotton candy or candied almonds.
R						OR5*
L				SUGAR1A	$PROD	OR5*	TONSILS1A*
M				zuckerwatte		oder	mandel

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Types ID	Gloss	HamNoSys	Mouth
13056	POWDER1A^		∅
2885	SALT1A		salz
88613	SALZGITTER1		salzgitter
44902	SEED6A		∅
42080	SAND1A		sand
45581	TO-SCATTER2A		∅
81960	WÜRZBURG1A		würzburg
3247	SUGAR1A		zucker