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:
Walder superó con comodidad al jamaicano James Beckford (segundo ayer, con 8,33) y se ha sumado a la lista de posibles medallistas en la ciudad andaluza.
Postion	Tokenization
1	Walder
2	superó
3	con
4	comodidad
5	al
6	jamaicano
7	James
8	Beckford
9	(
10	segundo
11	ayer
12	,
13	con
14	8,33
15	)
16	y
17	se
18	ha
19	sumado
20	a
21	la
22	lista
23	de
24	posibles
25	medallistas
26	en
27	la
28	ciudad
29	andaluza
30	.
Position	Tokenization	UPOS	Head	Deprel
1	Walder	PROPN	2	nsubj
2	superó	VERB	0	root
3	con	ADP	4	case
4	comodidad	NOUN	2	obl
5	al	ADP	6	case
6	jamaicano	NOUN	2	obj
7	James	PROPN	6	appos
8	Beckford	PROPN	7	flat
9	(	PUNCT	10	punct
10	segundo	ADJ	6	dep
11	ayer	ADV	10	advmod
12	,	PUNCT	10	punct
13	con	ADP	10	case
14	8,33	NUM	10	nummod
15	)	PUNCT	10	punct
16	y	CCONJ	19	cc
17	se	PRON	19	expl:pv
18	ha	AUX	19	aux
19	sumado	VERB	2	conj
20	a	ADP	22	case
21	la	DET	22	det
22	lista	NOUN	19	obj
23	de	ADP	25	case
24	posibles	ADJ	25	amod
25	medallistas	NOUN	22	nmod
26	en	ADP	28	case
27	la	DET	28	det
28	ciudad	NOUN	22	nmod
29	andaluza	ADJ	28	amod
30	.	PUNCT	2	punct