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 lanzador ciego de peso y de disco Alfonso Fidalgo, campeón olímpico en Barcelona92, Atlanta96 y Sydney2000 destacó la enorme sensación que se vive en el Estadio Olímpico.
Postion	Tokenization
1	El
2	lanzador
3	ciego
4	de
5	peso
6	y
7	de
8	disco
9	Alfonso
10	Fidalgo
11	,
12	campeón
13	olímpico
14	en
15	Barcelona92
16	,
17	Atlanta96
18	y
19	Sydney2000
20	destacó
21	la
22	enorme
23	sensación
24	que
25	se
26	vive
27	en
28	el
29	Estadio
30	Olímpico
31	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	lanzador	NOUN	20	nsubj
3	ciego	ADJ	2	amod
4	de	ADP	5	case
5	peso	NOUN	2	nmod
6	y	CCONJ	8	cc
7	de	ADP	8	case
8	disco	NOUN	5	conj
9	Alfonso	PROPN	2	appos
10	Fidalgo	PROPN	9	flat
11	,	PUNCT	12	punct
12	campeón	NOUN	2	appos
13	olímpico	ADJ	12	amod
14	en	ADP	15	case
15	Barcelona92	PROPN	12	nmod
16	,	PUNCT	17	punct
17	Atlanta96	PROPN	15	conj
18	y	CCONJ	19	cc
19	Sydney2000	PROPN	15	conj
20	destacó	VERB	0	root
21	la	DET	23	det
22	enorme	ADJ	23	amod
23	sensación	NOUN	20	obj
24	que	PRON	26	nsubj
25	se	PRON	26	expl:pass
26	vive	VERB	23	acl
27	en	ADP	29	case
28	el	DET	29	det
29	Estadio	PROPN	26	obl
30	Olímpico	PROPN	29	flat
31	.	PUNCT	20	punct