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:
"Esta ciudad es una isla progresista en una Texas que es muy conservadora", explicó a EFE Travis, un médico de Austin, quien duda entre votar a Al Gore, en un sufragio que no serviría para nada, o apoyar a Ralph Nader en su intento de lograr el cinco por ciento de votos a nivel nacional.
Postion	Tokenization
1	"
2	Esta
3	ciudad
4	es
5	una
6	isla
7	progresista
8	en
9	una
10	Texas
11	que
12	es
13	muy
14	conservadora
15	"
16	,
17	explicó
18	a
19	EFE
20	Travis
21	,
22	un
23	médico
24	de
25	Austin
26	,
27	quien
28	duda
29	entre
30	votar
31	a
32	Al
33	Gore
34	,
35	en
36	un
37	sufragio
38	que
39	no
40	serviría
41	para
42	nada
43	,
44	o
45	apoyar
46	a
47	Ralph
48	Nader
49	en
50	su
51	intento
52	de
53	lograr
54	el
55	cinco
56	por
57	ciento
58	de
59	votos
60	a
61	nivel
62	nacional
63	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	6	punct
2	Esta	DET	3	det
3	ciudad	NOUN	6	nsubj
4	es	AUX	6	cop
5	una	DET	6	det
6	isla	NOUN	17	ccomp
7	progresista	ADJ	6	amod
8	en	ADP	10	case
9	una	DET	10	det
10	Texas	PROPN	6	obl
11	que	PRON	14	nsubj
12	es	AUX	14	cop
13	muy	ADV	14	advmod
14	conservadora	ADJ	10	acl
15	"	PUNCT	6	punct
16	,	PUNCT	6	punct
17	explicó	VERB	0	root
18	a	ADP	19	case
19	EFE	PROPN	17	iobj
20	Travis	PROPN	17	nsubj
21	,	PUNCT	23	punct
22	un	DET	23	det
23	médico	NOUN	20	appos
24	de	ADP	25	case
25	Austin	PROPN	23	nmod
26	,	PUNCT	23	punct
27	quien	PRON	28	nsubj
28	duda	VERB	20	acl
29	entre	ADP	30	mark
30	votar	VERB	28	xcomp
31	a	ADP	33	case
32	Al	ADP	33	case
33	Gore	PROPN	30	obj
34	,	PUNCT	37	punct
35	en	ADP	37	case
36	un	DET	37	det
37	sufragio	NOUN	30	obl
38	que	PRON	40	nsubj
39	no	ADV	40	advmod
40	serviría	VERB	37	acl
41	para	ADP	42	case
42	nada	PRON	40	obj
43	,	PUNCT	37	punct
44	o	CCONJ	45	cc
45	apoyar	VERB	30	conj
46	a	ADP	47	case
47	Ralph	PROPN	45	obj
48	Nader	PROPN	47	flat
49	en	ADP	51	case
50	su	DET	51	det
51	intento	NOUN	45	obl
52	de	ADP	53	mark
53	lograr	VERB	51	acl
54	el	DET	55	det
55	cinco	NUM	53	obj
56	por	ADP	57	case
57	ciento	NUM	55	compound
58	de	ADP	59	case
59	votos	NOUN	55	nmod
60	a	ADP	61	case
61	nivel	NOUN	53	obl
62	nacional	ADJ	61	amod
63	.	PUNCT	17	punct