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:
Y es que, aunque el gobernador de Texas supera en la mayoría de las encuestas al demócrata Al Gore, el margen de ventaja se ha reducido ligeramente en el último día de campaña.
Postion	Tokenization
1	Y
2	es
3	que
4	,
5	aunque
6	el
7	gobernador
8	de
9	Texas
10	supera
11	en
12	la
13	mayoría
14	de
15	las
16	encuestas
17	al
18	demócrata
19	Al
20	Gore
21	,
22	el
23	margen
24	de
25	ventaja
26	se
27	ha
28	reducido
29	ligeramente
30	en
31	el
32	último
33	día
34	de
35	campaña
36	.
Position	Tokenization	UPOS	Head	Deprel
1	Y	CCONJ	28	advmod
2	es	AUX	28	cop
3	que	SCONJ	28	mark
4	,	PUNCT	10	punct
5	aunque	SCONJ	10	mark
6	el	DET	7	det
7	gobernador	NOUN	10	nsubj
8	de	ADP	9	case
9	Texas	PROPN	7	nmod
10	supera	VERB	28	advcl
11	en	ADP	13	case
12	la	DET	13	det
13	mayoría	NOUN	10	obl
14	de	ADP	16	case
15	las	DET	16	det
16	encuestas	NOUN	13	nmod
17	al	ADP	18	case
18	demócrata	NOUN	10	obj
19	Al	ADP	20	case
20	Gore	PROPN	18	appos
21	,	PUNCT	10	punct
22	el	DET	23	det
23	margen	NOUN	28	nsubj
24	de	ADP	25	case
25	ventaja	NOUN	23	nmod
26	se	PRON	28	expl:pv
27	ha	AUX	28	aux
28	reducido	VERB	0	root
29	ligeramente	ADV	28	advmod
30	en	ADP	33	case
31	el	DET	33	det
32	último	ADJ	33	amod
33	día	NOUN	28	obl
34	de	ADP	35	case
35	campaña	NOUN	33	nmod
36	.	PUNCT	28	punct