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 marcha al Milan de Fernando Redondo, que, como él, apostó por Lorenzo Sanz durante el proceso electoral, fue abordada con suma cautela por el defensa madridista.
Postion	Tokenization
1	La
2	marcha
3	al
4	Milan
5	de
6	Fernando
7	Redondo
8	,
9	que
10	,
11	como
12	él
13	,
14	apostó
15	por
16	Lorenzo
17	Sanz
18	durante
19	el
20	proceso
21	electoral
22	,
23	fue
24	abordada
25	con
26	suma
27	cautela
28	por
29	el
30	defensa
31	madridista
32	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	marcha	NOUN	24	nsubj
3	al	ADP	4	case
4	Milan	PROPN	2	nmod
5	de	ADP	6	case
6	Fernando	PROPN	2	nmod
7	Redondo	PROPN	6	flat
8	,	PUNCT	14	punct
9	que	PRON	14	nsubj
10	,	PUNCT	12	punct
11	como	SCONJ	12	mark
12	él	PRON	14	obl
13	,	PUNCT	12	punct
14	apostó	VERB	6	acl
15	por	ADP	16	case
16	Lorenzo	PROPN	14	obj
17	Sanz	PROPN	16	flat
18	durante	ADP	20	case
19	el	DET	20	det
20	proceso	NOUN	14	obl
21	electoral	ADJ	20	amod
22	,	PUNCT	14	punct
23	fue	AUX	24	aux
24	abordada	VERB	0	root
25	con	ADP	26	case
26	suma	NOUN	24	obl
27	cautela	NOUN	26	nmod
28	por	ADP	30	case
29	el	DET	30	det
30	defensa	NOUN	24	obj
31	madridista	ADJ	30	amod
32	.	PUNCT	24	punct