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:
En cuanto a las cesiones de activos, el presidente dijo que el año que viene le reportarán 510 millones de euros, "el equivalente a las ayudas del Estado a CdF", que pierde cada año unos 915 millones de euros y acumula una deuda de 5.335 millones de euros.
Postion	Tokenization
1	En
2	cuanto
3	a
4	las
5	cesiones
6	de
7	activos
8	,
9	el
10	presidente
11	dijo
12	que
13	el
14	año
15	que
16	viene
17	le
18	reportarán
19	510
20	millones
21	de
22	euros
23	,
24	"
25	el
26	equivalente
27	a
28	las
29	ayudas
30	del
31	Estado
32	a
33	CdF
34	"
35	,
36	que
37	pierde
38	cada
39	año
40	unos
41	915
42	millones
43	de
44	euros
45	y
46	acumula
47	una
48	deuda
49	de
50	5.335
51	millones
52	de
53	euros
54	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	5	case
2	cuanto	NOUN	1	fixed
3	a	ADP	1	fixed
4	las	DET	5	det
5	cesiones	NOUN	11	obl
6	de	ADP	7	case
7	activos	NOUN	5	nmod
8	,	PUNCT	5	punct
9	el	DET	10	det
10	presidente	NOUN	11	nsubj
11	dijo	VERB	0	root
12	que	SCONJ	18	mark
13	el	DET	14	det
14	año	NOUN	18	obl
15	que	PRON	16	nsubj
16	viene	VERB	14	acl
17	le	PRON	18	obj
18	reportarán	VERB	11	ccomp
19	510	NUM	20	nummod
20	millones	NOUN	18	obj
21	de	ADP	22	case
22	euros	NOUN	20	nmod
23	,	PUNCT	26	punct
24	"	PUNCT	26	punct
25	el	DET	26	det
26	equivalente	NOUN	20	appos
27	a	ADP	29	case
28	las	DET	29	det
29	ayudas	NOUN	26	nmod
30	del	ADP	31	case
31	Estado	PROPN	29	nmod
32	a	ADP	33	case
33	CdF	PROPN	18	obj
34	"	PUNCT	33	punct
35	,	PUNCT	37	punct
36	que	PRON	37	nsubj
37	pierde	VERB	33	acl
38	cada	DET	39	det
39	año	NOUN	37	obl
40	unos	PRON	41	nmod
41	915	NUM	42	nummod
42	millones	NOUN	37	obj
43	de	ADP	44	case
44	euros	NOUN	42	nmod
45	y	CCONJ	46	cc
46	acumula	VERB	37	conj
47	una	DET	48	det
48	deuda	NOUN	46	obj
49	de	ADP	51	case
50	5.335	NUM	51	nummod
51	millones	NOUN	48	nmod
52	de	ADP	53	case
53	euros	NOUN	51	nmod
54	.	PUNCT	11	punct