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:
Carlos Bardem estuvo ayer en Barcelona para presentar con el resto del equipo la película Código natural, un drama rural que entremezcla varias historias de amor, que se estrena mañana.
Postion	Tokenization
1	Carlos
2	Bardem
3	estuvo
4	ayer
5	en
6	Barcelona
7	para
8	presentar
9	con
10	el
11	resto
12	del
13	equipo
14	la
15	película
16	Código
17	natural
18	,
19	un
20	drama
21	rural
22	que
23	entremezcla
24	varias
25	historias
26	de
27	amor
28	,
29	que
30	se
31	estrena
32	mañana
33	.
Position	Tokenization	UPOS	Head	Deprel
1	Carlos	PROPN	3	nsubj
2	Bardem	PROPN	1	flat
3	estuvo	VERB	0	root
4	ayer	ADV	3	advmod
5	en	ADP	6	case
6	Barcelona	PROPN	3	obl
7	para	ADP	8	mark
8	presentar	VERB	3	advcl
9	con	ADP	11	case
10	el	DET	11	det
11	resto	NOUN	8	obl
12	del	ADP	13	case
13	equipo	NOUN	11	nmod
14	la	DET	15	det
15	película	NOUN	8	obj
16	Código	PROPN	15	appos
17	natural	PROPN	16	flat
18	,	PUNCT	20	punct
19	un	DET	20	det
20	drama	NOUN	15	appos
21	rural	ADJ	20	amod
22	que	PRON	23	nsubj
23	entremezcla	VERB	20	acl
24	varias	DET	25	det
25	historias	NOUN	23	obj
26	de	ADP	27	case
27	amor	NOUN	25	nmod
28	,	PUNCT	31	punct
29	que	PRON	31	nsubj
30	se	PRON	31	expl:pass
31	estrena	VERB	15	acl
32	mañana	ADV	31	advmod
33	.	PUNCT	3	punct