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:
Segura ha conseguido ahora más dinero, más medios, más coches para destrozar, mejores efectos especiales y el permiso de rodaje en Marbella, con lo que la película resulta más espectacular.
Postion	Tokenization
1	Segura
2	ha
3	conseguido
4	ahora
5	más
6	dinero
7	,
8	más
9	medios
10	,
11	más
12	coches
13	para
14	destrozar
15	,
16	mejores
17	efectos
18	especiales
19	y
20	el
21	permiso
22	de
23	rodaje
24	en
25	Marbella
26	,
27	con
28	lo
29	que
30	la
31	película
32	resulta
33	más
34	espectacular
35	.
Position	Tokenization	UPOS	Head	Deprel
1	Segura	PROPN	3	nsubj
2	ha	AUX	3	aux
3	conseguido	VERB	0	root
4	ahora	ADV	3	advmod
5	más	ADV	6	advmod
6	dinero	NOUN	3	obj
7	,	PUNCT	9	punct
8	más	ADV	9	advmod
9	medios	NOUN	6	appos
10	,	PUNCT	12	punct
11	más	ADV	12	advmod
12	coches	NOUN	6	appos
13	para	ADP	14	mark
14	destrozar	VERB	12	acl
15	,	PUNCT	17	punct
16	mejores	ADJ	17	amod
17	efectos	NOUN	6	appos
18	especiales	ADJ	17	amod
19	y	CCONJ	21	cc
20	el	DET	21	det
21	permiso	NOUN	6	conj
22	de	ADP	23	case
23	rodaje	NOUN	21	nmod
24	en	ADP	25	case
25	Marbella	PROPN	23	nmod
26	,	PUNCT	32	punct
27	con	ADP	32	mark
28	lo	PRON	32	det
29	que	PRON	32	obl
30	la	DET	31	det
31	película	NOUN	32	nsubj
32	resulta	VERB	3	advcl
33	más	ADV	34	advmod
34	espectacular	ADJ	32	obj
35	.	PUNCT	3	punct