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:
Nos pareció lógico; la formación MIR, empezando por el mismo examen de acceso, ha seleccionado siempre a quienes tienen más capacidad de adquirir y memorizar conocimientos.
Postion	Tokenization
1	Nos
2	pareció
3	lógico
4	;
5	la
6	formación
7	MIR
8	,
9	empezando
10	por
11	el
12	mismo
13	examen
14	de
15	acceso
16	,
17	ha
18	seleccionado
19	siempre
20	a
21	quienes
22	tienen
23	más
24	capacidad
25	de
26	adquirir
27	y
28	memorizar
29	conocimientos
30	.
Position	Tokenization	UPOS	Head	Deprel
1	Nos	PRON	2	iobj
2	pareció	VERB	0	root
3	lógico	ADJ	2	xcomp
4	;	PUNCT	18	punct
5	la	DET	6	det
6	formación	NOUN	18	nsubj
7	MIR	PROPN	6	appos
8	,	PUNCT	9	punct
9	empezando	VERB	6	acl
10	por	ADP	13	case
11	el	DET	13	det
12	mismo	DET	11	det
13	examen	NOUN	9	obl
14	de	ADP	15	case
15	acceso	NOUN	13	nmod
16	,	PUNCT	9	punct
17	ha	AUX	18	aux
18	seleccionado	VERB	3	advcl
19	siempre	ADV	18	advmod
20	a	ADP	22	mark
21	quienes	PRON	22	nsubj
22	tienen	VERB	18	ccomp
23	más	ADV	24	advmod
24	capacidad	NOUN	22	obj
25	de	ADP	26	mark
26	adquirir	VERB	24	acl
27	y	CCONJ	28	cc
28	memorizar	VERB	26	conj
29	conocimientos	NOUN	26	obj
30	.	PUNCT	2	punct