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 want to go to thailand to do my boob job from South Africa but looking for the cheapest surgeons yet also good in his artwork on a humans body .
Postion	Tokenization
1	I
2	want
3	to
4	go
5	to
6	thailand
7	to
8	do
9	my
10	boob
11	job
12	from
13	South
14	Africa
15	but
16	looking
17	for
18	the
19	cheapest
20	surgeons
21	yet
22	also
23	good
24	in
25	his
26	artwork
27	on
28	a
29	humans
30	human
31	s
32	body
33	.
Position	Tokenization	UPOS	Head	Deprel
1	I	PRON	2	nsubj
2	want	VERB	0	root
3	to	PART	4	mark
4	go	VERB	2	xcomp
5	to	ADP	6	case
6	thailand	PROPN	4	obl
7	to	PART	8	mark
8	do	VERB	4	advcl
9	my	PRON	11	nmod:poss
10	boob	NOUN	11	compound
11	job	NOUN	8	obj
12	from	ADP	14	case
13	South	PROPN	14	compound
14	Africa	PROPN	4	obl
15	but	CCONJ	16	cc
16	looking	VERB	2	conj
17	for	ADP	20	case
18	the	DET	20	det
19	cheapest	ADJ	20	amod
20	surgeons	NOUN	16	obl
21	yet	ADV	23	advmod
22	also	ADV	23	advmod
23	good	ADJ	20	amod
24	in	ADP	26	case
25	his	PRON	26	nmod:poss
26	artwork	NOUN	23	obl
27	on	ADP	31	case
28	a	DET	29	det
29	humans	_	None	_
30	human	NOUN	31	nmod:poss
31	s	PART	29	case
32	body	NOUN	26	nmod
33	.	PUNCT	2	punct