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 ex tenista Steffi Graf ha decidido saldar finalmente sus cuentas con el fisco alemán, aceptando pagar cerca de 2.500 millones de pesetas, según explica el diario alemán Bild.
Postion	Tokenization
1	La
2	ex
3	tenista
4	Steffi
5	Graf
6	ha
7	decidido
8	saldar
9	finalmente
10	sus
11	cuentas
12	con
13	el
14	fisco
15	alemán
16	,
17	aceptando
18	pagar
19	cerca
20	de
21	2.500
22	millones
23	de
24	pesetas
25	,
26	según
27	explica
28	el
29	diario
30	alemán
31	Bild
32	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	3	det
2	ex	ADJ	3	amod
3	tenista	NOUN	7	nsubj
4	Steffi	PROPN	3	appos
5	Graf	PROPN	4	flat
6	ha	AUX	7	aux
7	decidido	VERB	0	root
8	saldar	VERB	7	xcomp
9	finalmente	ADV	8	advmod
10	sus	DET	11	det
11	cuentas	NOUN	8	obj
12	con	ADP	14	case
13	el	DET	14	det
14	fisco	NOUN	11	nmod
15	alemán	ADJ	14	amod
16	,	PUNCT	17	punct
17	aceptando	VERB	8	advcl
18	pagar	VERB	17	xcomp
19	cerca	ADV	22	advmod
20	de	ADP	19	fixed
21	2.500	NUM	22	nummod
22	millones	NOUN	18	obj
23	de	ADP	24	case
24	pesetas	NOUN	22	nmod
25	,	PUNCT	27	punct
26	según	SCONJ	27	mark
27	explica	VERB	7	advcl
28	el	DET	29	det
29	diario	NOUN	27	nsubj
30	alemán	ADJ	29	amod
31	Bild	PROPN	29	appos
32	.	PUNCT	7	punct