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:
El presidente de Telefónica, Juan Villalonga, estaba ayer muy orgulloso por el fichaje del comisario europeo Martin Bangemann, al que denominó "nuestro Ronaldo".
Postion	Tokenization
1	El
2	presidente
3	de
4	Telefónica
5	,
6	Juan
7	Villalonga
8	,
9	estaba
10	ayer
11	muy
12	orgulloso
13	por
14	el
15	fichaje
16	del
17	comisario
18	europeo
19	Martin
20	Bangemann
21	,
22	al
23	que
24	denominó
25	"
26	nuestro
27	Ronaldo
28	"
29	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	presidente	NOUN	12	nsubj
3	de	ADP	4	case
4	Telefónica	PROPN	2	nmod
5	,	PUNCT	6	punct
6	Juan	PROPN	2	appos
7	Villalonga	PROPN	6	flat
8	,	PUNCT	6	punct
9	estaba	AUX	12	cop
10	ayer	ADV	12	advmod
11	muy	ADV	12	advmod
12	orgulloso	ADJ	0	root
13	por	ADP	15	case
14	el	DET	15	det
15	fichaje	NOUN	12	nmod
16	del	ADP	17	case
17	comisario	NOUN	15	nmod
18	europeo	ADJ	17	amod
19	Martin	PROPN	17	appos
20	Bangemann	PROPN	19	flat
21	,	PUNCT	24	punct
22	al	ADP	23	case
23	que	PRON	24	obj
24	denominó	VERB	17	acl
25	"	PUNCT	27	punct
26	nuestro	DET	27	det
27	Ronaldo	PROPN	24	obj
28	"	PUNCT	27	punct
29	.	PUNCT	12	punct