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:
Entre los intérpretes destaca Xavier Domingo, un médico de Tarragona que abandonó hace años su carrera para dedicarse a la vida bohemia y que en la película interpreta a un viejo mago que tiene un encuentro con una prostituta.
Postion	Tokenization
1	Entre
2	los
3	intérpretes
4	destaca
5	Xavier
6	Domingo
7	,
8	un
9	médico
10	de
11	Tarragona
12	que
13	abandonó
14	hace
15	años
16	su
17	carrera
18	para
19	dedicarse
20	dedicar
21	se
22	a
23	la
24	vida
25	bohemia
26	y
27	que
28	en
29	la
30	película
31	interpreta
32	a
33	un
34	viejo
35	mago
36	que
37	tiene
38	un
39	encuentro
40	con
41	una
42	prostituta
43	.
Position	Tokenization	UPOS	Head	Deprel
1	Entre	ADP	3	case
2	los	DET	3	det
3	intérpretes	NOUN	4	obl
4	destaca	VERB	0	root
5	Xavier	PROPN	4	nsubj
6	Domingo	PROPN	5	flat
7	,	PUNCT	9	punct
8	un	DET	9	det
9	médico	NOUN	5	appos
10	de	ADP	11	case
11	Tarragona	PROPN	9	nmod
12	que	PRON	13	nsubj
13	abandonó	VERB	9	acl
14	hace	VERB	13	advcl
15	años	NOUN	14	obj
16	su	DET	17	det
17	carrera	NOUN	13	obj
18	para	ADP	19	mark
19	dedicarse	_	None	_
20	dedicar	VERB	13	advcl
21	se	PRON	19	expl:pv
22	a	ADP	23	case
23	la	DET	23	det
24	vida	NOUN	19	obj
25	bohemia	ADJ	23	amod
26	y	CCONJ	30	cc
27	que	PRON	30	nsubj
28	en	ADP	29	case
29	la	DET	29	det
30	película	NOUN	30	obl
31	interpreta	VERB	13	conj
32	a	ADP	34	case
33	un	DET	34	det
34	viejo	ADJ	34	amod
35	mago	NOUN	30	obj
36	que	PRON	36	nsubj
37	tiene	VERB	34	acl
38	un	DET	38	det
39	encuentro	NOUN	36	obj
40	con	ADP	41	case
41	una	DET	41	det
42	prostituta	NOUN	38	nmod
43	.	PUNCT	4	punct