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:
Para corregir este déficit - - que contrasta con la fuerte inversión que España realiza en México - -, se ha organizado un foro empresarial al que asistirá el presidente Aznar.
Postion	Tokenization
1	Para
2	corregir
3	este
4	déficit
5	-
6	-
7	que
8	contrasta
9	con
10	la
11	fuerte
12	inversión
13	que
14	España
15	realiza
16	en
17	México
18	-
19	-
20	,
21	se
22	ha
23	organizado
24	un
25	foro
26	empresarial
27	al
28	que
29	asistirá
30	el
31	presidente
32	Aznar
33	.
Position	Tokenization	UPOS	Head	Deprel
1	Para	ADP	2	mark
2	corregir	VERB	23	advcl
3	este	DET	4	det
4	déficit	NOUN	2	obj
5	-	PUNCT	8	punct
6	-	PUNCT	8	punct
7	que	PRON	8	nsubj
8	contrasta	VERB	4	acl
9	con	ADP	12	case
10	la	DET	12	det
11	fuerte	ADJ	12	amod
12	inversión	NOUN	8	obj
13	que	PRON	15	obj
14	España	PROPN	15	nsubj
15	realiza	VERB	12	acl
16	en	ADP	17	case
17	México	PROPN	15	obl
18	-	PUNCT	8	punct
19	-	PUNCT	8	punct
20	,	PUNCT	2	punct
21	se	PRON	23	expl:pass
22	ha	AUX	23	aux
23	organizado	VERB	0	root
24	un	DET	25	det
25	foro	NOUN	23	nsubj
26	empresarial	ADJ	25	amod
27	al	ADP	28	case
28	que	PRON	29	obl
29	asistirá	VERB	25	acl
30	el	DET	31	det
31	presidente	NOUN	29	nsubj
32	Aznar	PROPN	31	appos
33	.	PUNCT	23	punct