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 una entrevista tras derrotar a la americana Kristina Brandi y para tratar de explicar cómo ella y su padre habían destituido a su entrenador, Tony Roche, utilizó 44 veces la conocida muletilla.
Postion	Tokenization
1	En
2	una
3	entrevista
4	tras
5	derrotar
6	a
7	la
8	americana
9	Kristina
10	Brandi
11	y
12	para
13	tratar
14	de
15	explicar
16	cómo
17	ella
18	y
19	su
20	padre
21	habían
22	destituido
23	a
24	su
25	entrenador
26	,
27	Tony
28	Roche
29	,
30	utilizó
31	44
32	veces
33	la
34	conocida
35	muletilla
36	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	3	case
2	una	DET	3	det
3	entrevista	NOUN	30	obl
4	tras	ADP	5	mark
5	derrotar	VERB	30	advcl
6	a	ADP	8	case
7	la	DET	8	det
8	americana	NOUN	5	obj
9	Kristina	PROPN	8	appos
10	Brandi	PROPN	9	flat
11	y	CCONJ	13	cc
12	para	ADP	13	mark
13	tratar	VERB	5	conj
14	de	ADP	15	mark
15	explicar	VERB	13	xcomp
16	cómo	PRON	22	obl
17	ella	PRON	22	nsubj
18	y	CCONJ	20	cc
19	su	DET	20	det
20	padre	NOUN	17	conj
21	habían	AUX	22	aux
22	destituido	VERB	15	ccomp
23	a	ADP	25	case
24	su	DET	25	det
25	entrenador	NOUN	22	obj
26	,	PUNCT	27	punct
27	Tony	PROPN	25	appos
28	Roche	PROPN	27	flat
29	,	PUNCT	27	punct
30	utilizó	VERB	0	root
31	44	NUM	32	nummod
32	veces	NOUN	30	obl
33	la	DET	35	det
34	conocida	ADJ	35	amod
35	muletilla	NOUN	30	obj
36	.	PUNCT	30	punct