CLOTHES1A^

	
	1390

frontal

45°

90°

from above

L				CLOTHES1A^*	DUTY5	WHATEVER3*	$GEST-DECLINE1^
≙ CLOTHES1A^ (22 tokens)
by transcript \| by glosses \| by right neighbours \| by left neighbours
1246329 1246329 \| 61+m That's why a soldier covered the stroller with his green coat.
R		SOLDIER2*	WHAT1A*	CLOTHES1A^*	TO-UNDRESS1	GREEN41*	TO-COVER-UP1
L					TO-UNDRESS1		TO-COVER-UP1
M		soldaten	was			grün
1419610-11552205-12003930 1419610-… \| 46-60f But why completely naked? Why couldn’t you be dressed? Why?
R	NAKED1*	NAKED2*	WHY2A*	CLOTHES1A^*	WHY2A	NAKED1*	WHY2A*
L	NAKED1*	NAKED2*				NAKED1*
M	nackt		warum	angezogen	warum		warum
1430592 1430592 \| 61+f There was a tailor shop in the hall where the deaf people were working, and there was a tailor shop for paraments, for the chasuble.
R	AREA1A^*		THERE-IS3*	CLOTHES1A^*	TAILOR1*	FOR1*	CHURCH2A
L	AREA1A^*	AND5	THERE-IS3*		TAILOR1*		CHURCH2A
M		und	gibt	paramente	schn{eiderei}	für	kirche
1176566 1176566 \| 61+m Formal wear is not required. The choice in clothes is up to oneself.
R				CLOTHES1A^*	DUTY5	WHATEVER3*	$GEST-DECLINE1^
M				kostümpflicht		egal	[MG]
1250721 1250721 \| 61+m Many people are too lazy to bring back their shopping trolleys and just leave them standing around somewhere.
R				CLOTHES1A^*	LAZY1	$PROD	WHATEVER1A*
L				CLOTHES1A^*
M				geschäft	faul	[MG]	[MG]
1430592 1430592 \| 61+f For the priest’s cassock, you know?
R			CHURCH2A*	CLOTHES1A^*	TO-KNOW-STH2B*	YOU1*	CLOTHES1A^*
L			CHURCH2A*	CLOTHES1A^*			CLOTHES1A^*
M				priestergewand	weißt du		priestergewand
1433543 1433543 \| 31-45m Bavarian Lederhosen, but in a modern version.
R				CLOTHES1A^*	LEATHER1B		LEATHER1B
L			$INDEX1	CLOTHES1A^*	LEATHER1B	BAVARIA1*	LEATHER1B
M				bayer{ische}	leder	bayer{ische}	lederhose»
1430592 1430592 \| 61+f There was a tailor shop in the hall where the deaf people were working, and there was a tailor shop for paraments, for the chasuble.
R	TAILOR1*	FOR1*	CHURCH2A	CLOTHES1A^*
L	TAILOR1*		CHURCH2A	CLOTHES1A^*
M	schn{eiderei}	für	kirche	messgewand
1178768 1178768 \| 61+m He's wearing make-up and is dressed up. It's great.
R		FACE1*	THEATRE6*	CLOTHES1A^*	SUPER1*
L			THEATRE6*	CLOTHES1A^*
M			theater	kostüm	[MG]
1251334 1251334 \| 46-60m Mondays through Fridays one wore a blue kerchief.
R		MONDAY1B*	UNTIL-OR-TO1	CLOTHES1A^*	BLUE18A	KNOT1*
L				CLOTHES1A^*		KNOT1*
M		montag	bis	freitag	blau
1291636 1291636 \| 61+m A policeman wearing a uniform walked up to me.
R	POLICE1A*	TO-RUN1	POLICE1A	CLOTHES1A^*	TO-RUN1
L		TO-RUN1		CLOTHES1A^*	TO-RUN1	TO-COME3*
M	polizei	[MG]	polizist	uniform	[MG]
1430592 1430592 \| 61+f For the priest’s cassock, you know?
R	CLOTHES1A^*	TO-KNOW-STH2B*	YOU1*	CLOTHES1A^*
L	CLOTHES1A^*			CLOTHES1A^*
M	priestergewand	weißt du		priestergewand
1291164 1291164 \| 61+f I was curious and wanted to have a look for myself, but a costume is expensive.
R	HOW-QUESTION1*	ALL2A*	$GEST^	CLOTHES1A^*	EXPENSIVE1	MUCH5*
L	HOW-QUESTION1*		$GEST^	CLOTHES1A^*
M	wie				[MG]	viel
1582205 1582205 \| 18-30m The fall of the Berlin Wall happened over 20 years ago and we actually should all be the same, but still we use these words.
R	$NUM-TENS2A:2d*	YEAR2A	LIKE2*	CLOTHES1A^*	ALTHOUGH2*	WORD3*
L				CLOTHES1A^*
M	zwanzig	jahre	wie	leben	obwohl	wort wort
1178147 1178147 \| 46-60f Other people, who attended all the galas, told me that they thought the one in Munich was the best.
R	MUNICH1A*	GOOD1*	GALA1*	CLOTHES1A^*	GOOD1*
L	MUNICH1A*		GALA1*	CLOTHES1A^*	GOOD1*
M	münchen				[MG]
1246329 1246329 \| 61+m Then I saw two men in green rubber coats.
R	$GEST-OFF1^	LIKE1A*	MATERIAL1B^	CLOTHES1A^*	GREEN41
L	$GEST-OFF1^		MATERIAL1B^	CLOTHES1A^*
M		wie	gummi	mantel	grün
1178768 1178768 \| 61+m His costumes are really great.
R		$INDEX1*	BUT1*	CLOTHES1A^	SUPER1
L				CLOTHES1A^
M			aber	kostüme	[MG]
1291164 1291164 \| 61+f If you get this medal, you have to pay for everything.
R		$PROD	$PROD	CLOTHES1A^	SELF1A*	TO-PAY8B	$GEST-OFF1^
L			$INDEX1	CLOTHES1A^			$GEST-OFF1^
M		[MG]	[MG]		muss selbst	bezahlen
1248505 1248505 \| 31-45f In order for the gowns to keep their color, the room has to be very dark.
R	DARK1*	$INDEX1*	LIGHT1	CLOTHES1A^	BRIGHT2	NOT3A*	$GEST-OFF1^*
L	DARK1*			CLOTHES1A^	BRIGHT2	NOT3A*	$GEST-OFF1^*
M	dunkel		licht	farbe	hell	nicht
1178768 1178768 \| 61+f He was dressed like a woman and that was eye-catching.
R	$GEST-OFF1^	AS3	WOMAN1A	CLOTHES1A^	TO-BE-EYE-CATCHING1*
L	$GEST-OFF1^			CLOTHES1A^	TO-BE-EYE-CATCHING1*
M		als	frau	verkleiden	[MG]
1249741 1249741 \| 18-30f For instance, they showed what sports wear used to look like during that time.
R		$LIST1:2of2d	SPORTS1A		HOW-QUESTION2	TO-SHOW1A*	INVOLVED1A*
L	ALSO1A	$LIST1:2of2d	SPORTS1A	CLOTHES1A^*	HOW-QUESTION2	TO-SHOW1A*	INVOLVED1A*
M	auch	oder	sport	[MG]	wie	zeigen	auch dabei
1418889 1418889 \| 31-45f Then I wanted to, err you know, decorate shop windows professionally, things like that.
R				CLOTHES1A^*	TRADE-OR-INDUSTRIAL-ARTS1B*	RAG1
L		$INDEX1	$GEST-TO-PONDER1^	CLOTHES1A^*	TRADE-OR-INDUSTRIAL-ARTS1B*	RAG1	$INDEX1*
M					gewerbe		schaufenster»
= RAG1 (2 tokens)
Mouth: klamotten
frontal 45° 90° from above
Translational equivalent: rag
by transcript \| by glosses \| by right neighbours \| by left neighbours
1418903 1418903 \| 46-60f I met him and I saw right away that he was an unconventional type and that he dressed accordingly.
R	LIKE1A*	TOLERANT1*	LIKE1A*	RAG1		DISTINCT1*	$PROD
L				RAG1	$GEST-OFF1^*	DISTINCT1*
M	wie		wie	klamott		[MG]	[MG]
1418889 1418889 \| 31-45f Then I wanted to, err you know, decorate shop windows professionally, things like that.
R		CLOTHES1A^*	TRADE-OR-INDUSTRIAL-ARTS1B*	RAG1		TO-LOOK1	TO-CUT-WITH-SCISSORS2*
L	$GEST-TO-PONDER1^	CLOTHES1A^*	TRADE-OR-INDUSTRIAL-ARTS1B*	RAG1	$INDEX1*	$INDEX1	TO-CUT-WITH-SCISSORS2*
M			gewerbe		schaufenster
= CLOTHES1A (53 tokens)
Mouth: kleidung
frontal 45° 90° from above
Translational equivalents: clothing; clothes; to dress; apparel
by transcript \| by glosses \| by right neighbours \| by left neighbours
1181455 1181455 \| 61+f I didn't buy it.
R				CLOTHES1A*	TO-BUY1A*	$GEST-OFF1^
L					TO-BUY1A*	$GEST-OFF1^
M				klei{dung}	kaufen
1427725 1427725 \| 18-30f It means that the clothes stay the way they are.
R		$INDEX1	MEANING1*	CLOTHES1A*	RIGHT-OR-AGREED1^*
L			MEANING1*		RIGHT-OR-AGREED1^*
M			bedeutet
1248862 1248862 \| 18-30f I looked at her in surprise, because usually, when getting surgery, you get scrubs.
R	TYPICAL1*	TO-GIVE-HOLD-ON-TO1A*	$PROD	CLOTHES1A*	$PROD	TO-GIVE1*
L	TYPICAL1*	TO-GIVE-HOLD-ON-TO1A*	$PROD		$PROD	TO-GIVE1*
M	typisch	geben				geben
1413925 1413925 \| 61+f I got dressed and walked to the subway station.
R				CLOTHES1A*	I2	DEPARTURE1	SUBWAY1A
L				CLOTHES1A*		DEPARTURE1	SUBWAY1A
M						[MG]	u-bahn
1582205 1582205 \| 18-30m Clothes are the same, too.
R			CLOTHES5A*	CLOTHES1A*	EQUAL8*
L			CLOTHES5A*	CLOTHES1A*
M			klamo{tten}		wie
1582205 1582205 \| 18-30m I was wearing normal clothes, too.
R			USUAL1*	CLOTHES1A*	$GEST^
L			USUAL1*	CLOTHES1A*	$GEST^
M			normale	klamotten
1181455 1181455 \| 61+f I once found something nice to wear, but if you look at the price tag, you see it costs 300 to 600 euros.
R			AN1A	CLOTHES1A*	BEAUTIFUL3	I1	$INDEX1
L				CLOTHES1A*
M			ein	kleidung	schön		[MG]
1291164 1291164 \| 61+f I think a costume is very very expensive if you can’t sow it yourself.
R			AND1*	CLOTHES1A*	$INDEX1	EXPENSIVE2A	VERY7
L				CLOTHES1A*
M			und	kleidung	oh	teuer
1427725 1427725 \| 18-30f I used to think that I had to match the weather, for example I thought once the winter time arrives and it gets cold outside, you would have to wear a modern jacket.
R	COHERENCE1B	EXAMPLE1	FUTURE2*	CLOTHES1A*	I1*	COLD1	I1*
L	COHERENCE1B	EXAMPLE1		CLOTHES1A*		COLD1
M			zukunft			[LM:brr]
1249542 1249542 \| 46-60m You were able to buy things at the exhibitions, for example clothes or pictures.
R	DISTINCT1	TO-BUY1A	$GEST-OFF1^*	CLOTHES1A*	PICTURE4*	DISTINCT1	EXHIBITION1*
L	DISTINCT1	TO-BUY1A	$GEST-OFF1^*	CLOTHES1A*	PICTURE4*	DISTINCT1
M	verschieden				bilder	verschieden
1204694 1204694 \| 61+f I ask if I may and if they allow me to change their clothes and put on fresh ones.
R	CLOTHES5A	OFF-OR-TO-REMOVE-STH1A*	FRESH1	CLOTHES1A*
L	CLOTHES5A	OFF-OR-TO-REMOVE-STH1A*	FRESH1	CLOTHES1A*
M			frisch
1413703 1413703 \| 46-60m There is a clothes store in the capital of Tunisia, no, in the second largest city - Sousse - that is run by a deaf person.
R	DEAF1A*	STORE1*	TO-SELL1	CLOTHES1A*
L	DEAF1A*	STORE1*	TO-SELL1	CLOTHES1A*
M		geschäft
1427725 1427725 \| 18-30f Everything is in one color and that's it.
R		$NUM-ONE-TO-TEN1B:1d	COLOUR1A*	CLOTHES1A*	DONE4
L			COLOUR1A*	CLOTHES1A*	DONE4
M		ein	farb		[MG]
1427725 1427725 \| 18-30f Maybe you'll dress up a whole window mannequin with your clothes and you are just dressed with your underwear.
R		MAYBE1	FUTURE1B*	CLOTHES1A*	IN-ADDITION-MORE-AND-MORE1	PERSON2A*	I2
L				CLOTHES1A*	IN-ADDITION-MORE-AND-MORE1	PERSON2A*
M		viellei{cht}	zukunft
1251334 1251334 \| 46-60m Right, it’s the same thing, today we had to wear black.
R		SAME2A*	BLACK3	CLOTHES1A*	$GEST-OFF1^	$GEST-NM-NOD-HEAD1^
L		SAME2A*		CLOTHES1A*	$GEST-OFF1^	$GEST-NM-NOD-HEAD1^
M		selbe	schwarz
1182062 1182062 \| 46-60f They were veiled and were wearing scarfs. But/
R		MORE1*	MASK2B*	CLOTHES1A*	BUT1*
L		MORE1*		CLOTHES1A*
M		mehr			aber
1248625-15324720-15465943 1248625-… \| 31-45f There is a flea market where clothes are being sold.
R	$LIST1:3of3d	SPORTS1^*	CAN2A^	CLOTHES1A*	TO-SELL1*	OFF-OR-TO-REMOVE-STH2^
L	$LIST1:3of3d	SPORTS1^*	CAN2A^	CLOTHES1A*	TO-SELL1*
M		flohmarkt			verkauf
1413703 1413703 \| 46-60m So, I was able to buy a lot of stuff for little money because I’m deaf, and he gave me a discount.
R	$INDEX1	TO-KNOW-STH-OR-SB1A*	$INDEX1	CLOTHES1A*	OBJECT-ON-NECKLACE1^	$INDEX1	I2
L				CLOTHES1A*
M		kenn
1418903 1418903 \| 46-60f On top of that, he was dressed really unconventionally while exercising the sport.
R	I2	TO-LOOK-AT2*	AND3*	CLOTHES1A*	$PROD
L			AND3*	CLOTHES1A*	$PROD
M			und		[MG]
1427725 1427725 \| 18-30m They wore transparent satin.
R	TRANSPARENT1	TO-SEE1	SILK1A	CLOTHES1A*	I1
L	TRANSPARENT1		SILK1A	CLOTHES1A*
M	durchsichtig		seide
1427725 1427725 \| 18-30m How she dresses and everything?
R	$ALPHA1:L	PERSON1^	$INDEX1	CLOTHES1A*	$INDEX1
L				CLOTHES1A*
M	lady gaga
1582642 1582642 \| 18-30m She is wearing like a kitchen apron.
R	APRON2*	HOUSEHOLD1B	APRON1*	CLOTHES1A*
L	APRON2*	HOUSEHOLD1B	APRON1*	CLOTHES1A*
M	[MG]	haushaltsschürze
1427725 1427725 \| 18-30f We were supposed to express our identity through our clothing.
R	HIS-HER1	IDENTITY1A	MY1	CLOTHES1A*	LIKE-THIS1A*	$GEST-OFF1^	COHERENCE1B
L				CLOTHES1A*	LIKE-THIS1A*	$GEST-OFF1^	COHERENCE1B
M			wie		so
1206172 1206172 \| 46-60f His son leans onto the tub, in which his father is lying fully dressed, and reads in the book as well.
R	GOOD1*	FATHER1*	WET1A	CLOTHES1A*	TUB2	$PROD	TO-SIT1A*
L	GOOD1*	FATHER1*	WET1A	CLOTHES1A*	TUB2	$PROD	TO-SIT1A*
M	[MG]	vater			wann
1984213 1984213 \| 61+m The monkey collects money, it’s wearing a hat and a nice uniform.
R	LIKE1A*	TO-BEG1^	HAT4*	CLOTHES1A*	CLOTHES5B*	HAT2B*
L	LIKE1A*			CLOTHES1A*	CLOTHES5B*	HAT2B*
M	wie	bote		[MG]	uniform
1290121 1290121 \| 31-45m Now you can see a huge variety of cloths fans can choose from as well as many things fans come up with.
R	VERY7*	TO-FIND1A^*	SUPER1*	CLOTHES1A*	INTENSIVE3^*	SUPER1
L	VERY7*	TO-FIND1A^*		CLOTHES1A*	INTENSIVE3^*
M		extra	[MG]			[MG]
1418903 1418903 \| 31-45f A deaf dude who was dressed casually and in a cool manner. I instantly liked that and I started talking to him right away.
R	LOOSE1	TROUSERS1B	WAISTBELT1A	CLOTHES1A*			TO-PLEASE1
L	LOOSE1	TROUSERS1B	WAISTBELT1A	CLOTHES1A*	FANCY1	TO-LOOK-AT1^
M	locker		[MG]	[MG]			gefallen
1430592 1430592 \| 61+f I could do the simple things, but the more complicated designs were completely new to me.
R	CAN1*	BUT1*	TOLERANT1	CLOTHES1A*	I1	$GEST-OFF1^
L	CAN1*			CLOTHES1A*		$GEST-OFF1^
M	kann	aber	[MG]			[MG]
1205503 1205503 \| 61+f Whenever I feel good and I'm in a good mood, my plants reflect this emotional state.
R	MOOD3*	AMBIANCE5*	GOOD1	CLOTHES1A*	$GEST^	FLOWER1	$GEST-I-DONT-KNOW1^
L		AMBIANCE5*		CLOTHES1A*	$GEST^		$GEST-I-DONT-KNOW1^
M	stimm{ung}	[MG]	gut	laune		blume	[MG]
1245356 1245356 \| 61+m Still, I preferred to walk around like a blackguard.
R			SQUALID-OR-DEPRAVED1B*	CLOTHES1A*	$PROD
L	RATHER1	CROOK1		CLOTHES1A*	$PROD
M	am liebsten	lump	[MG]		[MG]
1204191 1204191 \| 61+m They paid attention to our manners when eating and to our cleanliness, and we had to make our own beds every morning.
R	DAILY2A*	TO-WASH-FACE1B*	$LIST1:3of3d	CLOTHES1A*	SELF1A	EVERYONE1A	TOMORROW1B
L	DAILY2A*	TO-WASH-FACE1B*	$LIST1:3of3d	CLOTHES1A*
M		waschen			selb{st}	jeden	morgen
1427725 1427725 \| 18-30f These days it's encouraged to dress according to your taste, to be open and to create your own look.
R	HIS-HER1	WHAT-DOES-THAT-MEAN1	TO-LOVE-STH2	CLOTHES1A*	IN-ADDITION-MORE-AND-MORE1
L				CLOTHES1A*	IN-ADDITION-MORE-AND-MORE1
M		was	[MG]
1584329-15450503-15475829 1584329-… \| 31-45m Then I hurry back to the car and put on my reflective vest.
R	TO-DRESS-UPPER-BODY2*	VEST1*	WAISTBELT1B^*	CLOTHES1A*	$GEST-NARRATION-SECTION-END1^
L	TO-DRESS-UPPER-BODY2*	VEST1*	WAISTBELT1B^*	CLOTHES1A*	$GEST-NARRATION-SECTION-END1^
M
1250270 1250270 \| 46-60f She looks good. Hair, cleavage, her outfit looks good.
R	CLOTHES3	GOOD1*	TO-SEE1	CLOTHES1A*
L	CLOTHES3			CLOTHES1A*
M	[MG]	gut	aus{sehen}
1413703 1413703 \| 46-60m At the market place at the city center, you’ll see a large square. That’s where the t-shirt shop is; it has t-shirts with logos on them.
R	RIGHT1			CLOTHES1A*	OBJECT-ON-NECKLACE1^
L	RIGHT1	COMPANY1A*	$INDEX1	CLOTHES1A*
M
1248505 1248505 \| 31-45f They moved there, and all of Diana's dresses are gone now.
R				CLOTHES1A	AND2A*	DRESS1	OFF1A*
L				CLOTHES1A	AND2A*	DRESS1
M					wohn	kleid	ab ab ab
1427725 1427725 \| 18-30m The people covered themselves up out of shame and they put on some thicker clothes.
R				CLOTHES1A	$PROD	$PROD	$PROD
L				CLOTHES1A	$PROD
M				[MG]	[MG]	[MG]	[MG]
1182062 1182062 \| 46-60f The clothes are exquisite and there’s marble and pillars everywhere.
R				CLOTHES1A	TO-COST2B*	A-WHOLE-LOT2*	MASS-OF-PEOPLE-ACTIVE1^*
L				CLOTHES1A	TO-COST2B*	A-WHOLE-LOT2*	MASS-OF-PEOPLE-ACTIVE1^*
M						[MG]	marmor
1427725 1427725 \| 18-30m Some of them might be wealthier but everyone is eyed suspiciously.
R			RICH1A	CLOTHES1A	TO-SEE-EACH-OTHER1^*
L				CLOTHES1A	TO-SEE-EACH-OTHER1^*
M			[MG]
1582399-11073030-11154047 1582399-… \| 61+f She received suitcases with children’s clothing from a company in Freital.
R		CONTAINER3^	CHILD-BABY1	CLOTHES1A	THIS-AND-THAT1
L	SUITCASE1*	CONTAINER3^	CHILD-BABY1	CLOTHES1A	THIS-AND-THAT1
M	mit dem koffer		kinderbekleidung		verschieden
1427725 1427725 \| 18-30m Lady Gaga, though, was willing to accept offers for unusual outfits.
R	$GEST-OFF1^	$INDEX1	CRAZY1A	CLOTHES1A
L	$GEST-OFF1^			CLOTHES1A
M			[MG]
1413703 1413703 \| 46-60m So, I was able to buy a lot of stuff for little money because I’m deaf, and he gave me a discount.
R	TO-DECREASE1^*	TO-SHOP1	AMOUNT1A*	CLOTHES1A	I2
L	TO-DECREASE1^*	TO-SHOP1	AMOUNT1A*	CLOTHES1A
M
1427725 1427725 \| 18-30m Everyone buys clothes.
R		ALL3*	TO-BUY1A	CLOTHES1A
L			TO-BUY1A	CLOTHES1A
M		alle	kaufen
1182062 1182062 \| 46-60f Did you find clothes and stuff easily?
R		CLOSE-BY1^	TO-FIND1A*	CLOTHES1A	TO-FIND1A*
L		CLOSE-BY1^		CLOTHES1A
M		leicht	finden finden	kleidung	finden finden
1413703 1413703 \| 46-60m The quality is probably not very high.
R	$GEST-NM-SHAKE-HEAD1^	NOT3A*	QUALITY1B*	CLOTHES1A	NOT3B*	QUALITY1B	CLOTHES1A
L	$GEST-NM-SHAKE-HEAD1^		QUALITY1B*	CLOTHES1A		QUALITY1B	CLOTHES1A
M	aber	nicht	qualität		nicht	qualität
1248505 1248505 \| 31-45f I always looked through the papers to see what she was wearing at functions and how her family was pictured.
R	ALWAYS5A*	I1	TO-LEAF-THROUGH1*	CLOTHES1A	$GEST-OFF1^	TO-GREET2*	$GEST-OFF1^
L	ALWAYS5A*		TO-LEAF-THROUGH1*	CLOTHES1A	$GEST-OFF1^	TO-GREET2*	$GEST-OFF1^
M	immer					begrüßung
1246100 1246100 \| 18-30m Our goal was to establish a noticeable and visible symbol of identification through the color of our clothes.
R	AIM2*	LIKE1A*	IDENTITY1A*	CLOTHES1A	LIKE-HOW1B*	TO-SHOW1A*	TO-STRIKE1A
L	AIM2*			CLOTHES1A		TO-SHOW1A*
M	ziel	wie		[MG]	wie		auffällig
1427725 1427725 \| 18-30m There was some harsh criticism about the things she should and shouldn't wear.
R	TO-CRITICISE1A*	$INDEX1	BONKERS1	CLOTHES1A	TO-CRITICISE1B*	TO-CRITICISE1A*
L	TO-CRITICISE1A*			CLOTHES1A		TO-CRITICISE1A*
M	[MG]					[MG]
1413703 1413703 \| 46-60m The quality is probably not very high.
R	CLOTHES1A	NOT3B*	QUALITY1B	CLOTHES1A	NOT4*	QUALITY1B*
L	CLOTHES1A		QUALITY1B	CLOTHES1A		QUALITY1B*
M	qualität	nicht	qualität		[MG] nicht	qualität
1249542 1249542 \| 46-60m You were also able to buy clothes at the Gallaudet University.
R	$INDEX1	TO-OWN-TO-EXIST1^	TO-BUY1A*	CLOTHES1A
L			TO-BUY1A*	CLOTHES1A
M	universität	[MG]	kaufen
1291164 1291164 \| 61+f I think a costume is very very expensive if you can’t sow it yourself.
R	VERY7	SELF1A	TO-SEW1*	CLOTHES1A
L			TO-SEW1*	CLOTHES1A
M	teuer	selbst	nähen	kleider
1182062 1182062 \| 46-60f I could look at all kinds of clothes in the stores.
R	INTO2	$PROD	TO-LOOK1*		$PROD
L	INTO2		TO-LOOK1*	CLOTHES1A*
M			schau	kleidung
1181455 1181455 \| 61+f There's another story about a baby/
R			BABY1	CLOTHES1A*
L	ALSO3A	HISTORY-OR-STORY2*	BABY1	CLOTHES1A*	PAST-OR-BACK-THEN1*
M	auch	geschichte	baby
~ SHIRT1 (9 tokens)
Mouth: hemd
frontal 45° 90° from above
Translational equivalents: dress shirt; shirt
by transcript \| by glosses \| by right neighbours \| by left neighbours
1430592 1430592 \| 61+f We sewed simple shirts, aprons and skirts.
R			EASY1	SHIRT1*	SHIRT1	APRON1*	SKIRT1*
L			EASY1	SHIRT1*	SHIRT1	APRON1*	SKIRT1*
M				he{md}	oberhemd	schürze	rock
1251334 1251334 \| 46-60m On Mondays one wore a blue shirt.
R	BLUE18B*	MONDAY1A*	BLUE18B*	SHIRT1*
L			BLUE18B*	SHIRT1*
M		montag	blau
1250646 1250646 \| 61+f You didn’t keep your FDJ uniform, did you?
R				SHIRT1	TO-STORE1*
L			TO-OWN1	SHIRT1	TO-STORE1*	CROSS2B^*	YOU1*
M			[MG]	hemd	aufheben	f-d-j
1251334 1251334 \| 46-60m A white shirt.
R			WHITE11*	SHIRT1
L				SHIRT1
M			weiß	hemd
1251334 1251334 \| 46-60m Yes, a blue shirt and a red kerchief.
R			BLUE18A*	SHIRT1	RED1A	KNOT1*
L				SHIRT1		KNOT1*
M			blau	hemd	rot
1251334 1251334 \| 46-60m I wore a blue shirt.
R			BLUE18B*	SHIRT1	I1
L				SHIRT1
M			blau
2935384-11295937-11502021 2935384-… \| 61+m Sometime later, on a Sunday, I wanted to get a clean tie or a shirt.
R	$GEST-OFF1^	SHIRT2	NEW1A^	SHIRT1	I2
L	$GEST-OFF1^	SHIRT2	NEW1A^	SHIRT1		$GEST-OFF1^*
M	krawatte oder		frisch	hemd
1430592 1430592 \| 61+f We sewed simple shirts, aprons and skirts.
R		EASY1	SHIRT1*	SHIRT1	APRON1*	SKIRT1*	$GEST-OFF1^
L		EASY1	SHIRT1*	SHIRT1	APRON1*	SKIRT1*	$GEST-OFF1^
M			he{md}	oberhemd	schürze	rock
1251334 1251334 \| 46-60m No, a white shirt.
R		NO1A*	WHITE11*	SHIRT1
L				SHIRT1
M			weiß	hemd
~ SWEATER1 (4 tokens)
Mouth: pullover
frontal 45° 90° from above
Translational equivalent: sweater
by transcript \| by glosses \| by right neighbours \| by left neighbours
1251334 1251334 \| 46-60m Like for the taping today, we also had to put on sweaters like this, for the video.
R	SWEATER1	I1*	MOVIE1*	SWEATER1	$GEST-OFF1^
L	SWEATER1	I1*		SWEATER1	$GEST-OFF1^
M	pullover		film
1251334 1251334 \| 46-60m Like for the taping today, we also had to put on sweaters like this, for the video.
R	$INDEX1*	CLOTHES3	TO-BUY1A*	SWEATER1	I1*	MOVIE1*	SWEATER1
L	$INDEX1*	CLOTHES3		SWEATER1	I1*		SWEATER1
M				pullover		film»
1211082-13131933-13230433 1211082-… \| 46-60f The lady designs her own knitting pattern, as well. She invents them herself.
R	APPROXIMATELY1^*	$INDEX1*	$INDEX1	SWEATER1	TO-KNIT1	TO-INVENT1	TO-KNIT1
L			FEELING3*	SWEATER1	TO-KNIT1		TO-KNIT1
M	entwerfen			pullover
1211082-13131933-13230433 1211082-… \| 46-60f She even has a couple of knitters working for her, making sweaters and stuff.
R	PRESENT-OR-HERE1	APPROXIMATELY1^*	EXAMPLE1^*	SWEATER1
L			EXAMPLE1^*	SWEATER1
M	da	wie	pullover

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Types ID	Gloss	HamNoSys	Mouth
13557	CLOTHES1A^		∅
62485	RAG1		klamotten
2635	CLOTHES1A		kleidung
2595	SHIRT1		hemd
30407	SWEATER1		pullover