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:
Su principal rival es Drazen Budisa, aspirante de la coalición de socialdemócratas y liberales que lograron este mes la mayoría parlamentaria y quien, según las encuestas, conseguiría en torno al 21 por ciento de los sufragios, frente al 16 que obtendría el viceprimer ministro croata, Mate Granic.
Postion	Tokenization
1	Su
2	principal
3	rival
4	es
5	Drazen
6	Budisa
7	,
8	aspirante
9	de
10	la
11	coalición
12	de
13	socialdemócratas
14	y
15	liberales
16	que
17	lograron
18	este
19	mes
20	la
21	mayoría
22	parlamentaria
23	y
24	quien
25	,
26	según
27	las
28	encuestas
29	,
30	conseguiría
31	en
32	torno
33	al
34	21
35	por
36	ciento
37	de
38	los
39	sufragios
40	,
41	frente
42	al
43	16
44	que
45	obtendría
46	el
47	viceprimer
48	ministro
49	croata
50	,
51	Mate
52	Granic
53	.
Position	Tokenization	UPOS	Head	Deprel
1	Su	DET	3	det
2	principal	ADJ	3	amod
3	rival	NOUN	5	nsubj
4	es	AUX	5	cop
5	Drazen	PROPN	0	root
6	Budisa	PROPN	5	flat
7	,	PUNCT	8	punct
8	aspirante	NOUN	5	nmod
9	de	ADP	11	case
10	la	DET	11	det
11	coalición	NOUN	8	nmod
12	de	ADP	13	case
13	socialdemócratas	NOUN	11	nmod
14	y	CCONJ	15	cc
15	liberales	NOUN	13	conj
16	que	PRON	17	nsubj
17	lograron	VERB	13	acl
18	este	DET	19	det
19	mes	NOUN	17	obl
20	la	DET	21	det
21	mayoría	NOUN	17	obj
22	parlamentaria	ADJ	21	amod
23	y	CCONJ	30	cc
24	quien	PRON	30	nsubj
25	,	PUNCT	28	punct
26	según	ADP	28	case
27	las	DET	28	det
28	encuestas	NOUN	30	obl
29	,	PUNCT	28	punct
30	conseguiría	VERB	8	conj
31	en	ADP	34	case
32	torno	NOUN	31	fixed
33	al	ADP	31	fixed
34	21	NUM	30	obj
35	por	ADP	36	case
36	ciento	NUM	34	compound
37	de	ADP	39	case
38	los	DET	39	det
39	sufragios	NOUN	34	nmod
40	,	PUNCT	43	punct
41	frente	NOUN	43	case
42	al	ADP	41	fixed
43	16	NUM	30	obl
44	que	PRON	45	obj
45	obtendría	VERB	43	advcl
46	el	DET	48	det
47	viceprimer	ADJ	48	amod
48	ministro	NOUN	45	nsubj
49	croata	ADJ	48	amod
50	,	PUNCT	51	punct
51	Mate	PROPN	48	appos
52	Granic	PROPN	51	flat
53	.	PUNCT	5	punct