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 letrado John Warden considera que la propuesta del Gobierno convertiría a Microsoft en "la nica compañía del mundo que no ganará, no podrá ganar, la próxima ronda de competencia" en la industria de los programas informáticos.
Postion	Tokenization
1	El
2	letrado
3	John
4	Warden
5	considera
6	que
7	la
8	propuesta
9	del
10	Gobierno
11	convertiría
12	a
13	Microsoft
14	en
15	"
16	la
17	nica
18	compañía
19	del
20	mundo
21	que
22	no
23	ganará
24	,
25	no
26	podrá
27	ganar
28	,
29	la
30	próxima
31	ronda
32	de
33	competencia
34	"
35	en
36	la
37	industria
38	de
39	los
40	programas
41	informáticos
42	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	letrado	NOUN	5	nsubj
3	John	PROPN	2	appos
4	Warden	PROPN	3	flat
5	considera	VERB	0	root
6	que	SCONJ	11	mark
7	la	DET	8	det
8	propuesta	NOUN	11	nsubj
9	del	ADP	10	case
10	Gobierno	PROPN	8	nmod
11	convertiría	VERB	5	ccomp
12	a	ADP	13	case
13	Microsoft	PROPN	11	obj
14	en	ADP	18	case
15	"	PUNCT	18	punct
16	la	DET	18	det
17	nica	ADJ	18	amod
18	compañía	NOUN	11	obj
19	del	ADP	20	case
20	mundo	NOUN	18	nmod
21	que	PRON	23	nsubj
22	no	ADV	23	advmod
23	ganará	VERB	18	acl
24	,	PUNCT	27	punct
25	no	ADV	27	advmod
26	podrá	AUX	27	aux
27	ganar	VERB	23	parataxis
28	,	PUNCT	27	punct
29	la	DET	31	det
30	próxima	ADJ	31	amod
31	ronda	NOUN	23	obj
32	de	ADP	33	case
33	competencia	NOUN	31	nmod
34	"	PUNCT	18	punct
35	en	ADP	37	case
36	la	DET	37	det
37	industria	NOUN	11	obl
38	de	ADP	40	case
39	los	DET	40	det
40	programas	NOUN	37	nmod
41	informáticos	ADJ	40	amod
42	.	PUNCT	5	punct