As a helpful and smart assistant, your task is to parse a given text in any language to Universal Dependency (UD) format including POS tags and dependency relations (HEAD and DEPREL).
Key Components of UD Annotation:
1. Tokens: The fundamental units within UD are tokens. These can be individual words, punctuation marks, or even parts of multi-word expressions. Each token has several associated attributes.
2. UPOS Tags: The UPOS field in the CoNLL-U format represents the universal part-of-speech tag assigned to each word. This tag is part of a universal POS tag set designed to be applicable across different languages. The UPOS tags include categories such as NOUN, VERB, ADJ (adjective), ADV (adverb), PRON (pronoun), DET (determiner), and more. 
3. Dependency Relations: Dependency relations are the core of the syntactic representation. They form a tree structure over the tokens in a sentence. Here's how they work:
    - HEAD: This field indicates the head of the current word. The head is the word that the current word is connected to in the dependency parse tree. The value is an integer that corresponds to the ID of the head word within the same sentence. A value of zero (0) indicates that the word is the root of the sentence.
    - DEPREL: The DEPREL field specifies the type of dependency relation between the current word and its head (as specified in the HEAD field). The value is a universal dependency relation or a language-specific subtype of such a relation.
Note: Blank lines are used to mark the boundaries between sentences.
Example:
Let's analyze this sentence with its UD annotation:
"The big dog chased the cat."
1. Tokenization:
- The
- big
- dog
- chased
- the
- cat
- .
2. UPOS Tags:
- The: DET
- big: ADJ
- dog: NOUN
- chased: VERB
- the: DET
- cat: NOUN
- .: PUNCT
3. Head node (parent):
- The: the parent of this word is "dog" at position 3
- big: the parent of this word is "dog" at position 3
- dog: the parent of this word is "chased" at position 4
- chased: this is the root node, therefore its head is 0
- the: the parent of this word is "cat" at position 6
- cat: the parent of this word is "chased" at position 4
- .: the parent of this word is "chased" at position 4
3. Dependency Relations:
- root(ROOT, chased)
- det(dog, The)
- amod(dog, big)
- nsubj(chased, dog)
- det(cat, the)
- obj(chased, cat)
Combining the above annotations, the final output in UD format is:
Position	Tokenization	UPOS	Head	Deprel
1	The	DET	3	det
2	big	ADJ	3	amod
3	dog	NOUN	4	nsubj
4	chased	VERB	0	ROOT
5	the	DET	6	det
6	cat	NOUN	4	obj
7	.	PUNCT	4	punct
Generate UD annotations for the following tokenized text:
Marek Dzida the owner and photographer puts whole heart in his business - If you are into old fashion (Not Digital) quality photography this is best place in Long Beach as I think not many folks can do affordable traditional photos anymore I know Marek personaly and I will always recommend him
Postion	Tokenization
1	Marek
2	Dzida
3	the
4	owner
5	and
6	photographer
7	puts
8	whole
9	heart
10	in
11	his
12	business
13	-
14	If
15	you
16	are
17	into
18	old
19	fashion
20	(
21	Not
22	Digital
23	)
24	quality
25	photography
26	this
27	is
28	best
29	place
30	in
31	Long
32	Beach
33	as
34	I
35	think
36	not
37	many
38	folks
39	can
40	do
41	affordable
42	traditional
43	photos
44	anymore
45	I
46	know
47	Marek
48	personaly
49	and
50	I
51	will
52	always
53	recommend
54	him
Position	Tokenization	UPOS	Head	Deprel
1	Marek	PROPN	7	nsubj
2	Dzida	PROPN	1	flat
3	the	DET	4	det
4	owner	NOUN	1	appos
5	and	CCONJ	6	cc
6	photographer	NOUN	4	conj
7	puts	VERB	0	root
8	whole	ADJ	9	amod
9	heart	NOUN	7	obj
10	in	ADP	12	case
11	his	PRON	12	nmod:poss
12	business	NOUN	7	obl
13	-	PUNCT	7	punct
14	If	SCONJ	25	mark
15	you	PRON	25	nsubj
16	are	AUX	25	cop
17	into	ADP	25	case
18	old	ADJ	19	amod
19	fashion	NOUN	25	amod
20	(	PUNCT	22	punct
21	Not	ADV	22	advmod
22	Digital	ADJ	19	parataxis
23	)	PUNCT	22	punct
24	quality	ADJ	25	amod
25	photography	NOUN	29	advcl
26	this	PRON	29	nsubj
27	is	AUX	29	cop
28	best	ADJ	29	amod
29	place	NOUN	7	parataxis
30	in	ADP	32	case
31	Long	PROPN	32	compound
32	Beach	PROPN	29	nmod
33	as	SCONJ	35	mark
34	I	PRON	35	nsubj
35	think	VERB	29	advcl
36	not	ADV	38	advmod
37	many	ADJ	38	amod
38	folks	NOUN	40	nsubj
39	can	AUX	40	aux
40	do	VERB	35	ccomp
41	affordable	ADJ	43	amod
42	traditional	ADJ	43	amod
43	photos	NOUN	40	obj
44	anymore	ADV	40	advmod
45	I	PRON	46	nsubj
46	know	VERB	7	parataxis
47	Marek	PROPN	46	obj
48	personaly	ADV	46	advmod
49	and	CCONJ	53	cc
50	I	PRON	53	nsubj
51	will	AUX	53	aux
52	always	ADV	53	advmod
53	recommend	VERB	46	conj
54	him	PRON	53	obj