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:
En el bando demócrata, la pugna entre el vicepresidente Al Gore y el ex senador Bill Bradley se presentó más igualada, aunque Gore logró el 54% de los votos frente al 46% para Bradley, una diferencia que entraba dentro de los cálculos de Gore.
Postion	Tokenization
1	En
2	el
3	bando
4	demócrata
5	,
6	la
7	pugna
8	entre
9	el
10	vicepresidente
11	Al
12	Gore
13	y
14	el
15	ex
16	senador
17	Bill
18	Bradley
19	se
20	presentó
21	más
22	igualada
23	,
24	aunque
25	Gore
26	logró
27	el
28	54%
29	de
30	los
31	votos
32	frente
33	al
34	46%
35	para
36	Bradley
37	,
38	una
39	diferencia
40	que
41	entraba
42	dentro
43	de
44	los
45	cálculos
46	de
47	Gore
48	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	3	case
2	el	DET	3	det
3	bando	NOUN	20	obl
4	demócrata	ADJ	3	amod
5	,	PUNCT	3	punct
6	la	DET	7	det
7	pugna	NOUN	20	nsubj
8	entre	ADP	10	case
9	el	DET	10	det
10	vicepresidente	NOUN	7	nmod
11	Al	ADP	12	case
12	Gore	PROPN	10	appos
13	y	CCONJ	16	cc
14	el	DET	16	det
15	ex	ADJ	16	amod
16	senador	NOUN	10	conj
17	Bill	PROPN	16	appos
18	Bradley	PROPN	17	flat
19	se	PRON	20	obj
20	presentó	VERB	0	root
21	más	ADV	22	advmod
22	igualada	ADJ	20	obj
23	,	PUNCT	26	punct
24	aunque	SCONJ	26	mark
25	Gore	PROPN	26	nsubj
26	logró	VERB	20	advcl
27	el	DET	28	det
28	54%	SYM	26	obj
29	de	ADP	31	case
30	los	DET	31	det
31	votos	NOUN	28	nmod
32	frente	ADV	26	advmod
33	al	ADP	34	case
34	46%	SYM	32	obl
35	para	ADP	36	case
36	Bradley	PROPN	34	nmod
37	,	PUNCT	39	punct
38	una	DET	39	det
39	diferencia	NOUN	26	obl
40	que	PRON	41	nsubj
41	entraba	VERB	39	acl
42	dentro	ADV	41	advmod
43	de	ADP	45	case
44	los	DET	45	det
45	cálculos	NOUN	42	obl
46	de	ADP	47	case
47	Gore	PROPN	45	nmod
48	.	PUNCT	20	punct