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:
El intérprete, quien en el filme de Pérez Herrero encarna al malo de la historia, dijo que el cine siempre le encasilla "en personajes de matón y de gánster".
Postion	Tokenization
1	El
2	intérprete
3	,
4	quien
5	en
6	el
7	filme
8	de
9	Pérez
10	Herrero
11	encarna
12	al
13	malo
14	de
15	la
16	historia
17	,
18	dijo
19	que
20	el
21	cine
22	siempre
23	le
24	encasilla
25	"
26	en
27	personajes
28	de
29	matón
30	y
31	de
32	gánster
33	"
34	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	intérprete	NOUN	18	nsubj
3	,	PUNCT	11	punct
4	quien	PRON	11	nsubj
5	en	ADP	7	case
6	el	DET	7	det
7	filme	NOUN	11	obl
8	de	ADP	9	case
9	Pérez	PROPN	7	nmod
10	Herrero	PROPN	9	flat
11	encarna	VERB	2	acl
12	al	ADP	13	case
13	malo	ADJ	11	obj
14	de	ADP	16	case
15	la	DET	16	det
16	historia	NOUN	13	nmod
17	,	PUNCT	11	punct
18	dijo	VERB	0	root
19	que	SCONJ	24	mark
20	el	DET	21	det
21	cine	NOUN	24	nsubj
22	siempre	ADV	24	advmod
23	le	PRON	24	obj
24	encasilla	VERB	18	ccomp
25	"	PUNCT	27	punct
26	en	ADP	27	case
27	personajes	NOUN	24	obl
28	de	ADP	29	case
29	matón	NOUN	27	nmod
30	y	CCONJ	32	cc
31	de	ADP	32	case
32	gánster	NOUN	29	conj
33	"	PUNCT	27	punct
34	.	PUNCT	18	punct