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:
"Soy consciente de que en España se ha vivido intensamente esta medalla, porque hoy en Madrid la gente me paraba en la calle para darme la enhorabuena", declaró.
Postion	Tokenization
1	"
2	Soy
3	consciente
4	de
5	que
6	en
7	España
8	se
9	ha
10	vivido
11	intensamente
12	esta
13	medalla
14	,
15	porque
16	hoy
17	en
18	Madrid
19	la
20	gente
21	me
22	paraba
23	en
24	la
25	calle
26	para
27	darme
28	dar
29	me
30	la
31	enhorabuena
32	"
33	,
34	declaró
35	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	3	punct
2	Soy	AUX	3	cop
3	consciente	ADJ	33	ccomp
4	de	ADP	10	mark
5	que	SCONJ	10	mark
6	en	ADP	7	case
7	España	PROPN	10	obl
8	se	PRON	10	expl:pass
9	ha	AUX	10	aux
10	vivido	VERB	3	acl
11	intensamente	ADV	10	advmod
12	esta	DET	13	det
13	medalla	NOUN	10	nsubj
14	,	PUNCT	22	punct
15	porque	SCONJ	22	mark
16	hoy	ADV	22	advmod
17	en	ADP	18	case
18	Madrid	PROPN	22	obl
19	la	DET	20	det
20	gente	NOUN	22	nsubj
21	me	PRON	22	obj
22	paraba	VERB	3	advcl
23	en	ADP	25	case
24	la	DET	25	det
25	calle	NOUN	22	obl
26	para	ADP	27	mark
27	darme	_	None	_
28	dar	VERB	22	advcl
29	me	PRON	27	iobj
30	la	DET	30	det
31	enhorabuena	NOUN	27	obj
32	"	PUNCT	3	punct
33	,	PUNCT	3	punct
34	declaró	VERB	0	root
35	.	PUNCT	33	punct