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:
Ha sido, sin duda, el hombre de la eliminatoria para sonrojo de Frank de Boer, que no da con los resortes para realizar un marcaje eficaz a la estrella madridista.
Postion	Tokenization
1	Ha
2	sido
3	,
4	sin
5	duda
6	,
7	el
8	hombre
9	de
10	la
11	eliminatoria
12	para
13	sonrojo
14	de
15	Frank
16	de
17	Boer
18	,
19	que
20	no
21	da
22	con
23	los
24	resortes
25	para
26	realizar
27	un
28	marcaje
29	eficaz
30	a
31	la
32	estrella
33	madridista
34	.
Position	Tokenization	UPOS	Head	Deprel
1	Ha	AUX	8	aux
2	sido	AUX	8	cop
3	,	PUNCT	4	punct
4	sin	ADP	8	advmod
5	duda	NOUN	4	fixed
6	,	PUNCT	4	punct
7	el	DET	8	det
8	hombre	NOUN	0	root
9	de	ADP	11	case
10	la	DET	11	det
11	eliminatoria	NOUN	8	nmod
12	para	ADP	13	case
13	sonrojo	NOUN	8	obl
14	de	ADP	15	case
15	Frank	PROPN	13	nmod
16	de	ADP	17	case
17	Boer	PROPN	15	flat
18	,	PUNCT	21	punct
19	que	PRON	21	nsubj
20	no	ADV	21	advmod
21	da	VERB	15	acl
22	con	ADP	24	case
23	los	DET	24	det
24	resortes	NOUN	21	obj
25	para	ADP	26	mark
26	realizar	VERB	24	acl
27	un	DET	28	det
28	marcaje	NOUN	26	obj
29	eficaz	ADJ	28	amod
30	a	ADP	32	case
31	la	DET	32	det
32	estrella	NOUN	26	obj
33	madridista	ADJ	32	amod
34	.	PUNCT	8	punct