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 Museu d'Història de Catalunya recibió el pasado año la visita de 160.000 personas, una cifra que, según su nuevo director, Jaume Sobrequés, "debería aumentar una media anual de 50.000 visitantes".
Postion	Tokenization
1	El
2	Museu
3	d'Història
4	de
5	Catalunya
6	recibió
7	el
8	pasado
9	año
10	la
11	visita
12	de
13	160.000
14	personas
15	,
16	una
17	cifra
18	que
19	,
20	según
21	su
22	nuevo
23	director
24	,
25	Jaume
26	Sobrequés
27	,
28	"
29	debería
30	aumentar
31	una
32	media
33	anual
34	de
35	50.000
36	visitantes
37	"
38	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	Museu	PROPN	6	nsubj
3	d'Història	PROPN	2	flat
4	de	ADP	5	case
5	Catalunya	PROPN	2	nmod
6	recibió	VERB	0	root
7	el	DET	9	det
8	pasado	ADJ	9	amod
9	año	NOUN	6	obl
10	la	DET	11	det
11	visita	NOUN	6	obj
12	de	ADP	14	case
13	160.000	NUM	14	nummod
14	personas	NOUN	11	nmod
15	,	PUNCT	17	punct
16	una	DET	17	det
17	cifra	NOUN	14	appos
18	que	PRON	30	nsubj
19	,	PUNCT	23	punct
20	según	ADP	23	case
21	su	DET	23	det
22	nuevo	ADJ	23	amod
23	director	NOUN	30	obl
24	,	PUNCT	25	punct
25	Jaume	PROPN	23	appos
26	Sobrequés	PROPN	25	flat
27	,	PUNCT	25	punct
28	"	PUNCT	30	punct
29	debería	AUX	30	aux
30	aumentar	VERB	17	acl
31	una	DET	32	det
32	media	NOUN	30	obj
33	anual	ADJ	32	amod
34	de	ADP	36	case
35	50.000	NUM	36	nummod
36	visitantes	NOUN	32	nmod
37	"	PUNCT	30	punct
38	.	PUNCT	6	punct