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 presidente de la Generalitat, Jordi Pujol, respondió ayer a todas las críticas a la paga extra para los perceptores de pensiones no contributivas con el argumento de que lo importante de esta medida no era la cantidad, sino su impacto político y el cambio que ha provocado en la actitud del Gobierno de José María Aznar sobre la subida de todas las pensiones mínimas.
Postion	Tokenization
1	El
2	presidente
3	de
4	la
5	Generalitat
6	,
7	Jordi
8	Pujol
9	,
10	respondió
11	ayer
12	a
13	todas
14	las
15	críticas
16	a
17	la
18	paga
19	extra
20	para
21	los
22	perceptores
23	de
24	pensiones
25	no
26	contributivas
27	con
28	el
29	argumento
30	de
31	que
32	lo
33	importante
34	de
35	esta
36	medida
37	no
38	era
39	la
40	cantidad
41	,
42	sino
43	su
44	impacto
45	político
46	y
47	el
48	cambio
49	que
50	ha
51	provocado
52	en
53	la
54	actitud
55	del
56	Gobierno
57	de
58	José
59	María
60	Aznar
61	sobre
62	la
63	subida
64	de
65	todas
66	las
67	pensiones
68	mínimas
69	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	presidente	NOUN	10	nsubj
3	de	ADP	5	case
4	la	DET	5	det
5	Generalitat	PROPN	2	nmod
6	,	PUNCT	7	punct
7	Jordi	PROPN	2	appos
8	Pujol	PROPN	7	flat
9	,	PUNCT	7	punct
10	respondió	VERB	0	root
11	ayer	ADV	10	advmod
12	a	ADP	15	case
13	todas	DET	14	det
14	las	DET	15	det
15	críticas	NOUN	10	obj
16	a	ADP	18	case
17	la	DET	18	det
18	paga	NOUN	15	nmod
19	extra	ADJ	18	amod
20	para	ADP	22	case
21	los	DET	22	det
22	perceptores	NOUN	18	nmod
23	de	ADP	24	case
24	pensiones	NOUN	22	nmod
25	no	ADV	26	advmod
26	contributivas	ADJ	24	amod
27	con	ADP	29	case
28	el	DET	29	det
29	argumento	NOUN	10	obl
30	de	ADP	40	mark
31	que	SCONJ	40	mark
32	lo	PRON	33	det
33	importante	ADJ	40	nsubj
34	de	ADP	36	case
35	esta	DET	36	det
36	medida	NOUN	33	nmod
37	no	ADV	40	advmod
38	era	AUX	40	cop
39	la	DET	40	det
40	cantidad	NOUN	29	acl
41	,	PUNCT	44	punct
42	sino	CCONJ	44	cc
43	su	DET	44	det
44	impacto	NOUN	40	conj
45	político	ADJ	44	amod
46	y	CCONJ	48	cc
47	el	DET	48	det
48	cambio	NOUN	44	conj
49	que	PRON	51	obj
50	ha	AUX	51	aux
51	provocado	VERB	48	acl
52	en	ADP	54	case
53	la	DET	54	det
54	actitud	NOUN	51	obl
55	del	ADP	56	case
56	Gobierno	PROPN	54	nmod
57	de	ADP	58	case
58	José	PROPN	56	nmod
59	María	PROPN	58	flat
60	Aznar	PROPN	58	flat
61	sobre	ADP	63	case
62	la	DET	63	det
63	subida	NOUN	54	nmod
64	de	ADP	67	case
65	todas	DET	66	det
66	las	DET	67	det
67	pensiones	NOUN	63	nmod
68	mínimas	ADJ	67	amod
69	.	PUNCT	10	punct