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, cree necesario que el Gobierno agilice los permisos de residencia a los inmigrantes para poder responder a la falta de mano de obra en Cataluña que, según cálculos del Departamento de Trabajo, impide cubrir unos 23.000 empleos en diversos sectores.
Postion	Tokenization
1	El
2	presidente
3	de
4	la
5	Generalitat
6	,
7	Jordi
8	Pujol
9	,
10	cree
11	necesario
12	que
13	el
14	Gobierno
15	agilice
16	los
17	permisos
18	de
19	residencia
20	a
21	los
22	inmigrantes
23	para
24	poder
25	responder
26	a
27	la
28	falta
29	de
30	mano
31	de
32	obra
33	en
34	Cataluña
35	que
36	,
37	según
38	cálculos
39	del
40	Departamento
41	de
42	Trabajo
43	,
44	impide
45	cubrir
46	unos
47	23.000
48	empleos
49	en
50	diversos
51	sectores
52	.
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	cree	VERB	0	root
11	necesario	ADJ	10	iobj
12	que	SCONJ	15	mark
13	el	DET	14	det
14	Gobierno	PROPN	15	nsubj
15	agilice	VERB	10	ccomp
16	los	DET	17	det
17	permisos	NOUN	15	obj
18	de	ADP	19	case
19	residencia	NOUN	17	nmod
20	a	ADP	22	case
21	los	DET	22	det
22	inmigrantes	NOUN	15	obj
23	para	ADP	25	mark
24	poder	AUX	25	aux
25	responder	VERB	10	advcl
26	a	ADP	28	case
27	la	DET	28	det
28	falta	NOUN	25	obj
29	de	ADP	30	case
30	mano	NOUN	28	nmod
31	de	ADP	32	case
32	obra	NOUN	30	nmod
33	en	ADP	34	case
34	Cataluña	PROPN	28	nmod
35	que	PRON	44	nsubj
36	,	PUNCT	38	punct
37	según	ADP	38	case
38	cálculos	NOUN	44	obl
39	del	ADP	40	case
40	Departamento	PROPN	38	nmod
41	de	ADP	42	case
42	Trabajo	PROPN	40	flat
43	,	PUNCT	38	punct
44	impide	VERB	28	acl
45	cubrir	VERB	44	xcomp
46	unos	PRON	47	nmod
47	23.000	NUM	48	nummod
48	empleos	NOUN	45	obj
49	en	ADP	51	case
50	diversos	DET	51	det
51	sectores	NOUN	45	obl
52	.	PUNCT	10	punct