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:
It put hair on my chest and thanks to the owners advice I invested vanguard, got myself a woman like Jerry, and became a republican.
Postion	Tokenization
1	It
2	put
3	hair
4	on
5	my
6	chest
7	and
8	thanks
9	to
10	the
11	owners
12	owner
13	s
14	advice
15	I
16	invested
17	vanguard
18	,
19	got
20	myself
21	a
22	woman
23	like
24	Jerry
25	,
26	and
27	became
28	a
29	republican
30	.
Position	Tokenization	UPOS	Head	Deprel
1	It	PRON	2	nsubj
2	put	VERB	0	root
3	hair	NOUN	2	obj
4	on	ADP	6	case
5	my	PRON	6	nmod:poss
6	chest	NOUN	2	obl
7	and	CCONJ	15	cc
8	thanks	NOUN	15	obl:npmod
9	to	ADP	13	case
10	the	DET	11	det
11	owners	_	None	_
12	owner	NOUN	13	nmod:poss
13	s	PART	11	case
14	advice	NOUN	8	nmod
15	I	PRON	15	nsubj
16	invested	VERB	2	conj
17	vanguard	PROPN	15	obj
18	,	PUNCT	18	punct
19	got	VERB	15	conj
20	myself	PRON	18	iobj
21	a	DET	21	det
22	woman	NOUN	18	obj
23	like	ADP	23	case
24	Jerry	PROPN	21	nmod
25	,	PUNCT	26	punct
26	and	CCONJ	26	cc
27	became	VERB	15	conj
28	a	DET	28	det
29	republican	PROPN	26	xcomp
30	.	PUNCT	2	punct