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:
La peor entrevista: Se dice que Arantxa es una de las que utiliza más repetitivas frases como "You Know" (ya saben) pero hay alguien que gana a la española y es la australiana de origen serbio Jelena Dokic.
Postion	Tokenization
1	La
2	peor
3	entrevista
4	:
5	Se
6	dice
7	que
8	Arantxa
9	es
10	una
11	de
12	las
13	que
14	utiliza
15	más
16	repetitivas
17	frases
18	como
19	"
20	You
21	Know
22	"
23	(
24	ya
25	saben
26	)
27	pero
28	hay
29	alguien
30	que
31	gana
32	a
33	la
34	española
35	y
36	es
37	la
38	australiana
39	de
40	origen
41	serbio
42	Jelena
43	Dokic
44	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	3	det
2	peor	ADJ	3	amod
3	entrevista	NOUN	0	root
4	:	PUNCT	6	punct
5	Se	PRON	6	expl:pass
6	dice	VERB	3	acl
7	que	SCONJ	10	mark
8	Arantxa	PROPN	10	nsubj
9	es	AUX	10	cop
10	una	PRON	6	ccomp
11	de	ADP	14	mark
12	las	DET	14	det
13	que	PRON	14	nsubj
14	utiliza	VERB	10	acl
15	más	ADV	17	advmod
16	repetitivas	ADJ	17	amod
17	frases	NOUN	14	obj
18	como	SCONJ	20	mark
19	"	PUNCT	20	punct
20	You	NOUN	17	nmod
21	Know	NOUN	20	compound
22	"	PUNCT	20	punct
23	(	PUNCT	24	punct
24	ya	ADV	20	appos
25	saben	NOUN	24	compound
26	)	PUNCT	24	punct
27	pero	CCONJ	28	cc
28	hay	AUX	10	conj
29	alguien	PRON	28	obj
30	que	PRON	31	nsubj
31	gana	VERB	29	acl
32	a	ADP	34	case
33	la	DET	34	det
34	española	ADJ	31	obj
35	y	CCONJ	38	cc
36	es	AUX	38	cop
37	la	DET	38	det
38	australiana	NOUN	28	conj
39	de	ADP	40	case
40	origen	NOUN	38	nmod
41	serbio	ADJ	40	amod
42	Jelena	PROPN	38	appos
43	Dokic	PROPN	42	flat
44	.	PUNCT	3	punct