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:
Torrente 2 Misión en Marbella se construye entre chistes al más puro estilo Torrente - - mención especial para el que tiene como víctima a la modelo Esther Cañadas - -; persecuciones y referencias cómicas a la serie James Bond - - con José Luis Moreno, al parecer personaje reivindicable, ejerciendo de villano a lo Doctor No - - y desfile continuado de amigos del director.
Postion	Tokenization
1	Torrente
2	2
3	Misión
4	en
5	Marbella
6	se
7	construye
8	entre
9	chistes
10	al
11	más
12	puro
13	estilo
14	Torrente
15	-
16	-
17	mención
18	especial
19	para
20	el
21	que
22	tiene
23	como
24	víctima
25	a
26	la
27	modelo
28	Esther
29	Cañadas
30	-
31	-
32	;
33	persecuciones
34	y
35	referencias
36	cómicas
37	a
38	la
39	serie
40	James
41	Bond
42	-
43	-
44	con
45	José
46	Luis
47	Moreno
48	,
49	al
50	parecer
51	personaje
52	reivindicable
53	,
54	ejerciendo
55	de
56	villano
57	a
58	lo
59	Doctor
60	No
61	-
62	-
63	y
64	desfile
65	continuado
66	de
67	amigos
68	del
69	director
70	.
Position	Tokenization	UPOS	Head	Deprel
1	Torrente	PROPN	7	nsubj
2	2	NUM	1	nummod
3	Misión	PROPN	1	flat
4	en	ADP	5	case
5	Marbella	PROPN	1	flat
6	se	PRON	7	expl:pass
7	construye	VERB	0	root
8	entre	ADP	9	case
9	chistes	NOUN	7	obl
10	al	ADP	13	case
11	más	ADV	12	advmod
12	puro	ADJ	13	amod
13	estilo	NOUN	9	nmod
14	Torrente	PROPN	13	nmod
15	-	PUNCT	17	punct
16	-	PUNCT	17	punct
17	mención	NOUN	9	dep
18	especial	ADJ	17	amod
19	para	ADP	22	mark
20	el	DET	22	det
21	que	PRON	22	nsubj
22	tiene	VERB	17	acl
23	como	SCONJ	24	mark
24	víctima	NOUN	22	obj
25	a	ADP	27	case
26	la	DET	27	det
27	modelo	NOUN	22	obj
28	Esther	PROPN	27	appos
29	Cañadas	PROPN	28	flat
30	-	PUNCT	17	punct
31	-	PUNCT	17	punct
32	;	PUNCT	33	punct
33	persecuciones	NOUN	9	conj
34	y	CCONJ	35	cc
35	referencias	NOUN	33	conj
36	cómicas	ADJ	35	amod
37	a	ADP	39	case
38	la	DET	39	det
39	serie	NOUN	35	nmod
40	James	PROPN	39	appos
41	Bond	PROPN	40	flat
42	-	PUNCT	45	punct
43	-	PUNCT	45	punct
44	con	ADP	45	case
45	José	PROPN	35	nmod
46	Luis	PROPN	45	flat
47	Moreno	PROPN	45	flat
48	,	PUNCT	51	punct
49	al	ADP	51	advmod
50	parecer	NOUN	49	fixed
51	personaje	NOUN	45	appos
52	reivindicable	ADJ	51	amod
53	,	PUNCT	54	punct
54	ejerciendo	VERB	45	acl
55	de	ADP	56	case
56	villano	NOUN	54	obl
57	a	ADP	59	case
58	lo	PRON	59	det
59	Doctor	PROPN	56	nmod
60	No	PART	59	flat
61	-	PUNCT	45	punct
62	-	PUNCT	45	punct
63	y	CCONJ	64	cc
64	desfile	NOUN	9	conj
65	continuado	ADJ	64	amod
66	de	ADP	67	case
67	amigos	NOUN	65	nmod
68	del	ADP	69	case
69	director	NOUN	67	nmod
70	.	PUNCT	7	punct