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 Partido Popular alcanzó la mayoría absoluta en Madrid y obtuvo 19 diputados, dos más que en 1996, con el 52,52 por ciento de los sufragios y 1.610.000 votos (al 99,83 % escrutado), lo que supone el mejor resultado del partido en Madrid desde la instauración de la democracia.
Postion	Tokenization
1	El
2	Partido
3	Popular
4	alcanzó
5	la
6	mayoría
7	absoluta
8	en
9	Madrid
10	y
11	obtuvo
12	19
13	diputados
14	,
15	dos
16	más
17	que
18	en
19	1996
20	,
21	con
22	el
23	52,52
24	por
25	ciento
26	de
27	los
28	sufragios
29	y
30	1.610.000
31	votos
32	(
33	al
34	99,83
35	%
36	escrutado
37	)
38	,
39	lo
40	que
41	supone
42	el
43	mejor
44	resultado
45	del
46	partido
47	en
48	Madrid
49	desde
50	la
51	instauración
52	de
53	la
54	democracia
55	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	Partido	PROPN	4	nsubj
3	Popular	PROPN	2	flat
4	alcanzó	VERB	0	root
5	la	DET	6	det
6	mayoría	NOUN	4	obj
7	absoluta	ADJ	6	amod
8	en	ADP	9	case
9	Madrid	PROPN	4	obl
10	y	CCONJ	11	cc
11	obtuvo	VERB	4	conj
12	19	NUM	13	nummod
13	diputados	NOUN	11	obj
14	,	PUNCT	15	punct
15	dos	NUM	13	appos
16	más	ADV	15	advmod
17	que	SCONJ	19	mark
18	en	ADP	19	case
19	1996	NOUN	15	obl
20	,	PUNCT	15	punct
21	con	ADP	23	case
22	el	DET	23	det
23	52,52	NUM	11	obl
24	por	ADP	25	case
25	ciento	NUM	23	compound
26	de	ADP	28	case
27	los	DET	28	det
28	sufragios	NOUN	23	nmod
29	y	CCONJ	31	cc
30	1.610.000	NUM	31	nummod
31	votos	NOUN	23	conj
32	(	PUNCT	34	punct
33	al	ADP	34	case
34	99,83	NUM	31	dep
35	%	SYM	34	nmod
36	escrutado	ADJ	34	advmod
37	)	PUNCT	34	punct
38	,	PUNCT	23	punct
39	lo	PRON	41	det
40	que	PRON	41	nsubj
41	supone	VERB	11	advcl
42	el	DET	44	det
43	mejor	ADJ	44	amod
44	resultado	NOUN	41	obj
45	del	ADP	46	case
46	partido	NOUN	44	nmod
47	en	ADP	48	case
48	Madrid	PROPN	44	nmod
49	desde	ADP	51	case
50	la	DET	51	det
51	instauración	NOUN	44	nmod
52	de	ADP	54	case
53	la	DET	54	det
54	democracia	NOUN	51	nmod
55	.	PUNCT	4	punct