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:
Aunque a regañadientes, Blatter tuvo que reconocer un descubierto de 51 millones de francos suizos 5.500 millones de pesetas, 33 millones de euros - - y hasta fue denunciado por fraude tras la desaparición de 8.000 millones de pesetas que la cadena O'Globo había pagado a ISL.
Postion	Tokenization
1	Aunque
2	a
3	regañadientes
4	,
5	Blatter
6	tuvo
7	que
8	reconocer
9	un
10	descubierto
11	de
12	51
13	millones
14	de
15	francos
16	suizos
17	5.500
18	millones
19	de
20	pesetas
21	,
22	33
23	millones
24	de
25	euros
26	-
27	-
28	y
29	hasta
30	fue
31	denunciado
32	por
33	fraude
34	tras
35	la
36	desaparición
37	de
38	8.000
39	millones
40	de
41	pesetas
42	que
43	la
44	cadena
45	O'Globo
46	había
47	pagado
48	a
49	ISL
50	.
Position	Tokenization	UPOS	Head	Deprel
1	Aunque	SCONJ	2	mark
2	a	ADP	8	advmod
3	regañadientes	NOUN	2	fixed
4	,	PUNCT	2	punct
5	Blatter	PROPN	8	nsubj
6	tuvo	VERB	0	root
7	que	SCONJ	8	cc
8	reconocer	VERB	6	conj
9	un	DET	10	det
10	descubierto	NOUN	8	obj
11	de	ADP	13	case
12	51	NUM	13	nummod
13	millones	NOUN	10	nmod
14	de	ADP	15	case
15	francos	NOUN	13	nmod
16	suizos	ADJ	15	amod
17	5.500	NUM	18	nummod
18	millones	NOUN	13	appos
19	de	ADP	20	case
20	pesetas	NOUN	18	nmod
21	,	PUNCT	23	punct
22	33	NUM	23	nummod
23	millones	NOUN	13	appos
24	de	ADP	25	case
25	euros	NOUN	23	nmod
26	-	PUNCT	31	punct
27	-	PUNCT	31	punct
28	y	CCONJ	31	cc
29	hasta	ADV	31	advmod
30	fue	AUX	31	aux
31	denunciado	VERB	6	conj
32	por	ADP	33	case
33	fraude	NOUN	31	obl
34	tras	ADP	36	case
35	la	DET	36	det
36	desaparición	NOUN	31	obl
37	de	ADP	39	case
38	8.000	NUM	39	nummod
39	millones	NOUN	36	nmod
40	de	ADP	41	case
41	pesetas	NOUN	39	nmod
42	que	PRON	47	obj
43	la	DET	44	det
44	cadena	NOUN	47	nsubj
45	O'Globo	PROPN	44	appos
46	había	AUX	47	aux
47	pagado	VERB	39	acl
48	a	ADP	49	case
49	ISL	PROPN	47	obj
50	.	PUNCT	6	punct