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:
I've had 2 cuts now from Georgia and have paid more in other salons/barbershops and have not received this kind of treatment or cut!
Postion	Tokenization
1	I've
2	I
3	've
4	had
5	2
6	cuts
7	now
8	from
9	Georgia
10	and
11	have
12	paid
13	more
14	in
15	other
16	salons
17	/
18	barbershops
19	and
20	have
21	not
22	received
23	this
24	kind
25	of
26	treatment
27	or
28	cut
29	!
Position	Tokenization	UPOS	Head	Deprel
1	I've	_	None	_
2	I	PRON	3	nsubj
3	've	AUX	3	aux
4	had	VERB	0	root
5	2	NUM	5	nummod
6	cuts	NOUN	3	obj
7	now	ADV	3	advmod
8	from	ADP	8	case
9	Georgia	PROPN	3	obl
10	and	CCONJ	11	cc
11	have	AUX	11	aux
12	paid	VERB	3	conj
13	more	ADJ	11	obj
14	in	ADP	17	case
15	other	ADJ	17	amod
16	salons	NOUN	17	compound
17	/	SYM	17	cc
18	barbershops	NOUN	11	obl
19	and	CCONJ	21	cc
20	have	AUX	21	aux
21	not	PART	21	advmod
22	received	VERB	3	conj
23	this	DET	23	det
24	kind	NOUN	21	obj
25	of	ADP	25	case
26	treatment	NOUN	23	nmod
27	or	CCONJ	27	cc
28	cut	NOUN	25	conj
29	!	PUNCT	3	punct