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 director general de Tráfico, Carlos Muñoz Repiso, dijo que la normativa sobre las nuevas matrículas deberá conocerse antes de cinco o seis semanas, el tiempo que, en su opinión, tardará Madrid en agotar los aproximadamente 30.000 números que le quedan con el sistema de matriculación vigente.
Postion	Tokenization
1	El
2	director
3	general
4	de
5	Tráfico
6	,
7	Carlos
8	Muñoz
9	Repiso
10	,
11	dijo
12	que
13	la
14	normativa
15	sobre
16	las
17	nuevas
18	matrículas
19	deberá
20	conocerse
21	conocer
22	se
23	antes
24	de
25	cinco
26	o
27	seis
28	semanas
29	,
30	el
31	tiempo
32	que
33	,
34	en
35	su
36	opinión
37	,
38	tardará
39	Madrid
40	en
41	agotar
42	los
43	aproximadamente
44	30.000
45	números
46	que
47	le
48	quedan
49	con
50	el
51	sistema
52	de
53	matriculación
54	vigente
55	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	director	NOUN	11	nsubj
3	general	ADJ	2	amod
4	de	ADP	5	case
5	Tráfico	PROPN	2	nmod
6	,	PUNCT	7	punct
7	Carlos	PROPN	2	appos
8	Muñoz	PROPN	7	flat
9	Repiso	PROPN	7	flat
10	,	PUNCT	7	punct
11	dijo	VERB	0	root
12	que	SCONJ	20	mark
13	la	DET	14	det
14	normativa	NOUN	20	nsubj
15	sobre	ADP	18	case
16	las	DET	18	det
17	nuevas	ADJ	18	amod
18	matrículas	NOUN	14	nmod
19	deberá	AUX	20	aux
20	conocerse	_	None	_
21	conocer	VERB	11	ccomp
22	se	PRON	20	expl:pass
23	antes	ADV	20	advmod
24	de	ADP	27	case
25	cinco	NUM	27	nummod
26	o	CCONJ	26	cc
27	seis	NUM	24	conj
28	semanas	NOUN	22	obl
29	,	PUNCT	30	punct
30	el	DET	30	det
31	tiempo	NOUN	27	appos
32	que	PRON	37	obl
33	,	PUNCT	35	punct
34	en	ADP	35	case
35	su	DET	35	det
36	opinión	NOUN	37	obl
37	,	PUNCT	35	punct
38	tardará	VERB	30	acl
39	Madrid	PROPN	37	nsubj
40	en	ADP	40	mark
41	agotar	VERB	37	xcomp
42	los	DET	43	det
43	aproximadamente	ADV	43	advmod
44	30.000	NUM	44	nummod
45	números	NOUN	40	obj
46	que	PRON	47	nsubj
47	le	PRON	47	obj
48	quedan	VERB	44	acl
49	con	ADP	50	case
50	el	DET	50	det
51	sistema	NOUN	47	obl
52	de	ADP	52	case
53	matriculación	NOUN	50	nmod
54	vigente	ADJ	52	amod
55	.	PUNCT	11	punct