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:
MÁS de UN 85% de los trabajadores del sector del metal de Berlín y Brandeburgo apoyaron ayer una convocatoria de huelga para defender un aumento de los salarios del 6,5%.
Postion	Tokenization
1	MÁS
2	de
3	UN
4	85%
5	de
6	los
7	trabajadores
8	del
9	sector
10	del
11	metal
12	de
13	Berlín
14	y
15	Brandeburgo
16	apoyaron
17	ayer
18	una
19	convocatoria
20	de
21	huelga
22	para
23	defender
24	un
25	aumento
26	de
27	los
28	salarios
29	del
30	6,5%
31	.
Position	Tokenization	UPOS	Head	Deprel
1	MÁS	ADV	4	advmod
2	de	ADP	4	case
3	UN	PRON	4	nmod
4	85%	SYM	7	nmod
5	de	ADP	4	case
6	los	DET	4	det
7	trabajadores	NOUN	16	nsubj
8	del	ADP	9	case
9	sector	NOUN	7	nmod
10	del	ADP	11	case
11	metal	NOUN	9	nmod
12	de	ADP	13	case
13	Berlín	PROPN	11	nmod
14	y	CCONJ	15	cc
15	Brandeburgo	PROPN	13	conj
16	apoyaron	VERB	0	root
17	ayer	ADV	16	advmod
18	una	DET	19	det
19	convocatoria	NOUN	16	obj
20	de	ADP	21	case
21	huelga	NOUN	19	nmod
22	para	ADP	23	mark
23	defender	VERB	16	advcl
24	un	DET	25	det
25	aumento	NOUN	23	obj
26	de	ADP	28	case
27	los	DET	28	det
28	salarios	NOUN	25	nmod
29	del	ADP	30	case
30	6,5%	SYM	25	nmod
31	.	PUNCT	16	punct