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:
Admitió que buena parte del impacto y éxito de esta película (premiada en los festivales de Locarno y Montreal) se debe al personaje de Izidore Serban, que se interpreta a sí mismo.
Postion	Tokenization
1	Admitió
2	que
3	buena
4	parte
5	del
6	impacto
7	y
8	éxito
9	de
10	esta
11	película
12	(
13	premiada
14	en
15	los
16	festivales
17	de
18	Locarno
19	y
20	Montreal
21	)
22	se
23	debe
24	al
25	personaje
26	de
27	Izidore
28	Serban
29	,
30	que
31	se
32	interpreta
33	a
34	sí
35	mismo
36	.
Position	Tokenization	UPOS	Head	Deprel
1	Admitió	VERB	0	root
2	que	SCONJ	23	mark
3	buena	ADJ	4	amod
4	parte	NOUN	23	nsubj
5	del	ADP	6	case
6	impacto	NOUN	4	nmod
7	y	CCONJ	8	cc
8	éxito	NOUN	6	conj
9	de	ADP	11	case
10	esta	DET	11	det
11	película	NOUN	6	nmod
12	(	PUNCT	13	punct
13	premiada	ADJ	11	amod
14	en	ADP	16	case
15	los	DET	16	det
16	festivales	NOUN	13	obl
17	de	ADP	18	case
18	Locarno	PROPN	16	nmod
19	y	CCONJ	20	cc
20	Montreal	PROPN	18	conj
21	)	PUNCT	13	punct
22	se	PRON	23	expl:pv
23	debe	VERB	1	ccomp
24	al	ADP	25	case
25	personaje	NOUN	23	obj
26	de	ADP	27	case
27	Izidore	PROPN	25	nmod
28	Serban	PROPN	27	flat
29	,	PUNCT	32	punct
30	que	PRON	32	nsubj
31	se	PRON	32	obj
32	interpreta	VERB	25	acl
33	a	ADP	34	case
34	sí	PRON	32	obj
35	mismo	ADJ	34	amod
36	.	PUNCT	1	punct