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 la bolsa de Madrid, el sector de comunicaciones fue el más beneficiado por las subidas, por el tirón de Telefónica, y ganó un 4,70 por ciento; seguido de nuevas tecnologías, que subió un 3,49 por ciento; bancos, un 1,54 por ciento, y alimentación, un 0,49 por ciento.
Postion	Tokenization
1	En
2	la
3	bolsa
4	de
5	Madrid
6	,
7	el
8	sector
9	de
10	comunicaciones
11	fue
12	el
13	más
14	beneficiado
15	por
16	las
17	subidas
18	,
19	por
20	el
21	tirón
22	de
23	Telefónica
24	,
25	y
26	ganó
27	un
28	4,70
29	por
30	ciento
31	;
32	seguido
33	de
34	nuevas
35	tecnologías
36	,
37	que
38	subió
39	un
40	3,49
41	por
42	ciento
43	;
44	bancos
45	,
46	un
47	1,54
48	por
49	ciento
50	,
51	y
52	alimentación
53	,
54	un
55	0,49
56	por
57	ciento
58	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	3	case
2	la	DET	3	det
3	bolsa	NOUN	14	obl
4	de	ADP	5	case
5	Madrid	PROPN	3	nmod
6	,	PUNCT	3	punct
7	el	DET	8	det
8	sector	NOUN	14	nsubj
9	de	ADP	10	case
10	comunicaciones	NOUN	8	nmod
11	fue	AUX	14	cop
12	el	DET	14	det
13	más	ADV	14	advmod
14	beneficiado	ADJ	0	root
15	por	ADP	17	case
16	las	DET	17	det
17	subidas	NOUN	14	obj
18	,	PUNCT	21	punct
19	por	ADP	21	case
20	el	DET	21	det
21	tirón	NOUN	17	conj
22	de	ADP	23	case
23	Telefónica	PROPN	21	nmod
24	,	PUNCT	26	punct
25	y	CCONJ	26	cc
26	ganó	VERB	14	conj
27	un	DET	28	det
28	4,70	NUM	26	obj
29	por	ADP	30	case
30	ciento	NUM	28	compound
31	;	PUNCT	32	punct
32	seguido	ADJ	26	obj
33	de	ADP	35	case
34	nuevas	ADJ	35	amod
35	tecnologías	NOUN	32	obj
36	,	PUNCT	38	punct
37	que	PRON	38	nsubj
38	subió	VERB	35	acl
39	un	DET	40	det
40	3,49	NUM	38	obj
41	por	ADP	42	case
42	ciento	NUM	40	compound
43	;	PUNCT	44	punct
44	bancos	NOUN	35	conj
45	,	PUNCT	47	punct
46	un	DET	47	det
47	1,54	NUM	44	nummod
48	por	ADP	49	case
49	ciento	NUM	47	compound
50	,	PUNCT	47	punct
51	y	CCONJ	52	cc
52	alimentación	NOUN	35	conj
53	,	PUNCT	55	punct
54	un	DET	55	det
55	0,49	NUM	52	nummod
56	por	ADP	57	case
57	ciento	NUM	55	compound
58	.	PUNCT	14	punct