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 alemán Markus Merk, que creyó más en las representaciones teatrales de los jugadores de la Fiorentina que en las del Valencia, señaló penalti y Mijatovic lo transformó, a pesar de que Cañizares adivinó la trayectoria y a punto estuvo de desviar el balón con la punta de los dedos.
Postion	Tokenization
1	El
2	alemán
3	Markus
4	Merk
5	,
6	que
7	creyó
8	más
9	en
10	las
11	representaciones
12	teatrales
13	de
14	los
15	jugadores
16	de
17	la
18	Fiorentina
19	que
20	en
21	las
22	del
23	Valencia
24	,
25	señaló
26	penalti
27	y
28	Mijatovic
29	lo
30	transformó
31	,
32	a
33	pesar
34	de
35	que
36	Cañizares
37	adivinó
38	la
39	trayectoria
40	y
41	a
42	punto
43	estuvo
44	de
45	desviar
46	el
47	balón
48	con
49	la
50	punta
51	de
52	los
53	dedos
54	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	alemán	NOUN	25	nsubj
3	Markus	PROPN	2	appos
4	Merk	PROPN	3	flat
5	,	PUNCT	7	punct
6	que	PRON	7	nsubj
7	creyó	VERB	2	acl
8	más	ADV	7	obj
9	en	ADP	8	case
10	las	DET	11	det
11	representaciones	NOUN	8	nmod
12	teatrales	ADJ	11	amod
13	de	ADP	15	case
14	los	DET	15	det
15	jugadores	NOUN	11	nmod
16	de	ADP	18	case
17	la	DET	18	det
18	Fiorentina	PROPN	15	nmod
19	que	SCONJ	21	mark
20	en	ADP	21	case
21	las	DET	8	det
22	del	ADP	21	case
23	Valencia	PROPN	21	obl
24	,	PUNCT	7	punct
25	señaló	VERB	0	root
26	penalti	NOUN	25	obj
27	y	CCONJ	30	cc
28	Mijatovic	PROPN	30	nsubj
29	lo	PRON	30	obj
30	transformó	VERB	25	conj
31	,	PUNCT	37	punct
32	a	ADP	37	mark
33	pesar	NOUN	32	fixed
34	de	ADP	32	fixed
35	que	SCONJ	32	fixed
36	Cañizares	PROPN	37	nsubj
37	adivinó	VERB	30	advcl
38	la	DET	39	det
39	trayectoria	NOUN	37	obj
40	y	CCONJ	41	cc
41	a	ADP	37	conj
42	punto	NOUN	41	fixed
43	estuvo	AUX	41	cop
44	de	ADP	45	mark
45	desviar	VERB	41	xcomp
46	el	DET	47	det
47	balón	NOUN	45	obj
48	con	ADP	50	case
49	la	DET	50	det
50	punta	NOUN	45	obl
51	de	ADP	53	case
52	los	DET	53	det
53	dedos	NOUN	50	nmod
54	.	PUNCT	25	punct