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:
Y Romario, tan sorprendente en la vida como en el área adversaria (la vida es un rea adversaria), hizo saber que se quedaba, entrenaba, se concentraba y quería ganar al Madrid.
Postion	Tokenization
1	Y
2	Romario
3	,
4	tan
5	sorprendente
6	en
7	la
8	vida
9	como
10	en
11	el
12	área
13	adversaria
14	(
15	la
16	vida
17	es
18	un
19	rea
20	adversaria
21	)
22	,
23	hizo
24	saber
25	que
26	se
27	quedaba
28	,
29	entrenaba
30	,
31	se
32	concentraba
33	y
34	quería
35	ganar
36	al
37	Madrid
38	.
Position	Tokenization	UPOS	Head	Deprel
1	Y	CCONJ	23	advmod
2	Romario	PROPN	23	nsubj
3	,	PUNCT	5	punct
4	tan	ADV	5	advmod
5	sorprendente	ADJ	2	amod
6	en	ADP	8	case
7	la	DET	8	det
8	vida	NOUN	5	nmod
9	como	SCONJ	12	mark
10	en	ADP	12	case
11	el	DET	12	det
12	área	NOUN	5	obl
13	adversaria	ADJ	12	amod
14	(	PUNCT	19	punct
15	la	DET	16	det
16	vida	NOUN	19	nsubj
17	es	AUX	19	cop
18	un	DET	19	det
19	rea	NOUN	12	parataxis
20	adversaria	ADJ	19	amod
21	)	PUNCT	19	punct
22	,	PUNCT	5	punct
23	hizo	VERB	0	root
24	saber	VERB	23	xcomp
25	que	SCONJ	27	mark
26	se	PRON	27	expl:pv
27	quedaba	VERB	24	ccomp
28	,	PUNCT	29	punct
29	entrenaba	VERB	27	advcl
30	,	PUNCT	32	punct
31	se	PRON	32	expl:pv
32	concentraba	VERB	27	advcl
33	y	CCONJ	34	cc
34	quería	VERB	27	conj
35	ganar	VERB	34	xcomp
36	al	ADP	37	case
37	Madrid	PROPN	35	obj
38	.	PUNCT	23	punct