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:
Beatriz Ferrer Salat es uno de los jinetes seleccionados para competir con el equipo español de hípica en la modalidad de doma en los Juegos Olímpicos de Sydney, confiesa, que tiene "muy difícil" acercarse a una medalla, pero piensa que "hacer una buena clasificación" será un pequeño homenaje a su padre
Postion	Tokenization
1	Beatriz
2	Ferrer
3	Salat
4	es
5	uno
6	de
7	los
8	jinetes
9	seleccionados
10	para
11	competir
12	con
13	el
14	equipo
15	español
16	de
17	hípica
18	en
19	la
20	modalidad
21	de
22	doma
23	en
24	los
25	Juegos
26	Olímpicos
27	de
28	Sydney
29	,
30	confiesa
31	,
32	que
33	tiene
34	"
35	muy
36	difícil
37	"
38	acercarse
39	acercar
40	se
41	a
42	una
43	medalla
44	,
45	pero
46	piensa
47	que
48	"
49	hacer
50	una
51	buena
52	clasificación
53	"
54	será
55	un
56	pequeño
57	homenaje
58	a
59	su
60	padre
Position	Tokenization	UPOS	Head	Deprel
1	Beatriz	PROPN	5	nsubj
2	Ferrer	PROPN	1	flat
3	Salat	PROPN	1	flat
4	es	AUX	5	cop
5	uno	PRON	0	root
6	de	ADP	8	case
7	los	DET	8	det
8	jinetes	NOUN	5	nmod
9	seleccionados	ADJ	8	amod
10	para	ADP	11	mark
11	competir	VERB	9	advcl
12	con	ADP	14	case
13	el	DET	14	det
14	equipo	NOUN	11	obj
15	español	ADJ	14	amod
16	de	ADP	17	case
17	hípica	NOUN	14	nmod
18	en	ADP	20	case
19	la	DET	20	det
20	modalidad	NOUN	11	obl
21	de	ADP	22	case
22	doma	NOUN	20	nmod
23	en	ADP	25	case
24	los	DET	25	det
25	Juegos	PROPN	11	obl
26	Olímpicos	PROPN	25	flat
27	de	ADP	28	case
28	Sydney	PROPN	25	nmod
29	,	PUNCT	5	punct
30	confiesa	VERB	5	advcl
31	,	PUNCT	33	punct
32	que	SCONJ	33	mark
33	tiene	VERB	30	ccomp
34	"	PUNCT	36	punct
35	muy	ADV	36	advmod
36	difícil	ADJ	33	advmod
37	"	PUNCT	36	punct
38	acercarse	_	None	_
39	acercar	VERB	33	xcomp
40	se	PRON	38	expl:pv
41	a	ADP	42	case
42	una	DET	42	det
43	medalla	NOUN	38	obl
44	,	PUNCT	45	punct
45	pero	CCONJ	45	cc
46	piensa	VERB	30	conj
47	que	SCONJ	56	mark
48	"	PUNCT	48	punct
49	hacer	VERB	56	csubj
50	una	DET	51	det
51	buena	ADJ	51	amod
52	clasificación	NOUN	48	obj
53	"	PUNCT	48	punct
54	será	AUX	56	cop
55	un	DET	56	det
56	pequeño	ADJ	56	amod
57	homenaje	NOUN	45	ccomp
58	a	ADP	59	case
59	su	DET	59	det
60	padre	NOUN	56	nmod