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 actuación: Sin duda la de Mark Roberts, el especialista en streaking, que sonrojó a la rusa Anna Kournikova en la pista 14 al saltar y desnudarse delante de ella en cuanto escuchó la voz del juez de silla "bolas nuevas".
Postion	Tokenization
1	La
2	peor
3	actuación
4	:
5	Sin
6	duda
7	la
8	de
9	Mark
10	Roberts
11	,
12	el
13	especialista
14	en
15	streaking
16	,
17	que
18	sonrojó
19	a
20	la
21	rusa
22	Anna
23	Kournikova
24	en
25	la
26	pista
27	14
28	al
29	saltar
30	y
31	desnudarse
32	desnudar
33	se
34	delante
35	de
36	ella
37	en
38	cuanto
39	escuchó
40	la
41	voz
42	del
43	juez
44	de
45	silla
46	"
47	bolas
48	nuevas
49	"
50	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	3	det
2	peor	ADJ	3	amod
3	actuación	NOUN	0	root
4	:	PUNCT	5	punct
5	Sin	ADP	3	appos
6	duda	NOUN	5	fixed
7	la	DET	5	det
8	de	ADP	5	case
9	Mark	PROPN	5	nmod
10	Roberts	PROPN	9	flat
11	,	PUNCT	13	punct
12	el	DET	13	det
13	especialista	NOUN	9	appos
14	en	ADP	15	case
15	streaking	NOUN	13	nmod
16	,	PUNCT	18	punct
17	que	PRON	18	nsubj
18	sonrojó	VERB	9	acl
19	a	ADP	22	case
20	la	DET	22	det
21	rusa	ADJ	22	amod
22	Anna	PROPN	18	obj
23	Kournikova	PROPN	22	flat
24	en	ADP	26	case
25	la	DET	26	det
26	pista	NOUN	18	obl
27	14	NUM	26	nummod
28	al	ADP	29	mark
29	saltar	VERB	18	advcl
30	y	CCONJ	31	cc
31	desnudarse	_	None	_
32	desnudar	VERB	29	conj
33	se	PRON	31	obj
34	delante	ADV	31	advmod
35	de	ADP	35	case
36	ella	PRON	33	obl
37	en	ADP	38	mark
38	cuanto	NOUN	36	fixed
39	escuchó	VERB	29	advcl
40	la	DET	40	det
41	voz	NOUN	38	obj
42	del	ADP	42	case
43	juez	NOUN	40	nmod
44	de	ADP	44	case
45	silla	NOUN	42	nmod
46	"	PUNCT	46	punct
47	bolas	NOUN	40	appos
48	nuevas	NOUN	46	compound
49	"	PUNCT	46	punct
50	.	PUNCT	3	punct