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 alcalde de La Seu y senador, Joan Ganyet (PSC), considera que el Gobierno del PP "vuelve a marginar" al Eix Pirinenc en las inversiones previstas para el 2002, al destinar "la ridícula cantidad de 8,3 millones".
Postion	Tokenization
1	El
2	alcalde
3	de
4	La
5	Seu
6	y
7	senador
8	,
9	Joan
10	Ganyet
11	(
12	PSC
13	)
14	,
15	considera
16	que
17	el
18	Gobierno
19	del
20	PP
21	"
22	vuelve
23	a
24	marginar
25	"
26	al
27	Eix
28	Pirinenc
29	en
30	las
31	inversiones
32	previstas
33	para
34	el
35	2002
36	,
37	al
38	destinar
39	"
40	la
41	ridícula
42	cantidad
43	de
44	8,3
45	millones
46	"
47	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	alcalde	NOUN	15	nsubj
3	de	ADP	5	case
4	La	DET	5	det
5	Seu	DET	2	nmod
6	y	CCONJ	7	cc
7	senador	NOUN	2	conj
8	,	PUNCT	9	punct
9	Joan	PROPN	2	appos
10	Ganyet	PROPN	9	flat
11	(	PUNCT	12	punct
12	PSC	PROPN	9	flat
13	)	PUNCT	12	punct
14	,	PUNCT	2	punct
15	considera	VERB	0	root
16	que	SCONJ	22	mark
17	el	DET	18	det
18	Gobierno	PROPN	22	nsubj
19	del	ADP	20	case
20	PP	PROPN	18	nmod
21	"	PUNCT	22	punct
22	vuelve	VERB	15	xcomp
23	a	ADP	24	mark
24	marginar	VERB	22	xcomp
25	"	PUNCT	27	punct
26	al	ADP	27	case
27	Eix	PROPN	22	obj
28	Pirinenc	PROPN	27	flat
29	en	ADP	31	case
30	las	DET	31	det
31	inversiones	NOUN	22	obl
32	previstas	ADJ	31	amod
33	para	ADP	35	case
34	el	DET	35	det
35	2002	NOUN	32	obl
36	,	PUNCT	38	punct
37	al	ADP	38	mark
38	destinar	VERB	24	advcl
39	"	PUNCT	42	punct
40	la	DET	42	det
41	ridícula	ADJ	42	amod
42	cantidad	NOUN	38	obj
43	de	ADP	45	case
44	8,3	NUM	45	nummod
45	millones	NOUN	42	nmod
46	"	PUNCT	42	punct
47	.	PUNCT	15	punct