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:
Ana García, que padece la discapacidad de cuadros distónicos, logró la plata en 400 estilos, mientras que Samuel Soler, con parálisis cerebral en 200 libres, Maria Teresa Perales, parapléjica que logró en 200 su segunda medalla, y Deborah Font, ciega parcial y con quince años la deportista más joven de los españoles, consiguieron los tres bronces.
Postion	Tokenization
1	Ana
2	García
3	,
4	que
5	padece
6	la
7	discapacidad
8	de
9	cuadros
10	distónicos
11	,
12	logró
13	la
14	plata
15	en
16	400
17	estilos
18	,
19	mientras
20	que
21	Samuel
22	Soler
23	,
24	con
25	parálisis
26	cerebral
27	en
28	200
29	libres
30	,
31	Maria
32	Teresa
33	Perales
34	,
35	parapléjica
36	que
37	logró
38	en
39	200
40	su
41	segunda
42	medalla
43	,
44	y
45	Deborah
46	Font
47	,
48	ciega
49	parcial
50	y
51	con
52	quince
53	años
54	la
55	deportista
56	más
57	joven
58	de
59	los
60	españoles
61	,
62	consiguieron
63	los
64	tres
65	bronces
66	.
Position	Tokenization	UPOS	Head	Deprel
1	Ana	PROPN	12	nsubj
2	García	PROPN	1	flat
3	,	PUNCT	5	punct
4	que	PRON	5	nsubj
5	padece	VERB	1	acl
6	la	DET	7	det
7	discapacidad	NOUN	5	obj
8	de	ADP	9	case
9	cuadros	NOUN	7	nmod
10	distónicos	ADJ	9	amod
11	,	PUNCT	5	punct
12	logró	VERB	19	parataxis
13	la	DET	14	det
14	plata	NOUN	12	obj
15	en	ADP	17	case
16	400	NUM	17	nummod
17	estilos	NOUN	12	obl
18	,	PUNCT	19	punct
19	mientras	CCONJ	0	root
20	que	SCONJ	19	fixed
21	Samuel	PROPN	62	nsubj
22	Soler	PROPN	21	flat
23	,	PUNCT	25	punct
24	con	ADP	25	case
25	parálisis	NOUN	21	nmod
26	cerebral	ADJ	25	amod
27	en	ADP	28	case
28	200	NUM	25	nummod
29	libres	ADJ	28	amod
30	,	PUNCT	31	punct
31	Maria	PROPN	21	conj
32	Teresa	PROPN	31	flat
33	Perales	PROPN	31	flat
34	,	PUNCT	35	punct
35	parapléjica	ADJ	31	amod
36	que	PRON	37	nsubj
37	logró	VERB	31	acl
38	en	ADP	39	case
39	200	NUM	37	obl
40	su	DET	42	det
41	segunda	ADJ	42	amod
42	medalla	NOUN	37	obj
43	,	PUNCT	31	punct
44	y	CCONJ	45	cc
45	Deborah	PROPN	21	conj
46	Font	PROPN	45	flat
47	,	PUNCT	45	punct
48	ciega	NOUN	45	appos
49	parcial	ADJ	48	amod
50	y	CCONJ	55	cc
51	con	ADP	53	case
52	quince	NUM	53	nummod
53	años	NOUN	55	nmod
54	la	DET	55	det
55	deportista	NOUN	48	conj
56	más	ADV	57	advmod
57	joven	ADJ	55	amod
58	de	ADP	60	case
59	los	DET	60	det
60	españoles	NOUN	57	nmod
61	,	PUNCT	21	punct
62	consiguieron	VERB	19	parataxis
63	los	DET	65	det
64	tres	NUM	63	nummod
65	bronces	NOUN	62	obj
66	.	PUNCT	19	punct