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:
Los parlamentarios también se han entrevistado durante el pasado fin de semana con la Autoridad Única del Estado de Vargas y con el ministro de Ciencia y Tecnología, Carlos Genatios, y con el gobernador de esa región, Alfredo Laya, la más castigada por las lluvias.
Postion	Tokenization
1	Los
2	parlamentarios
3	también
4	se
5	han
6	entrevistado
7	durante
8	el
9	pasado
10	fin
11	de
12	semana
13	con
14	la
15	Autoridad
16	Única
17	del
18	Estado
19	de
20	Vargas
21	y
22	con
23	el
24	ministro
25	de
26	Ciencia
27	y
28	Tecnología
29	,
30	Carlos
31	Genatios
32	,
33	y
34	con
35	el
36	gobernador
37	de
38	esa
39	región
40	,
41	Alfredo
42	Laya
43	,
44	la
45	más
46	castigada
47	por
48	las
49	lluvias
50	.
Position	Tokenization	UPOS	Head	Deprel
1	Los	DET	2	det
2	parlamentarios	NOUN	6	nsubj
3	también	ADV	6	advmod
4	se	PRON	6	expl:pv
5	han	AUX	6	aux
6	entrevistado	VERB	0	root
7	durante	ADP	10	case
8	el	DET	10	det
9	pasado	ADJ	10	amod
10	fin	NOUN	6	obl
11	de	ADP	12	case
12	semana	NOUN	10	nmod
13	con	ADP	15	case
14	la	DET	15	det
15	Autoridad	PROPN	6	obj
16	Única	PROPN	15	flat
17	del	ADP	18	case
18	Estado	PROPN	15	nmod
19	de	ADP	20	case
20	Vargas	PROPN	18	flat
21	y	CCONJ	24	cc
22	con	ADP	24	case
23	el	DET	24	det
24	ministro	NOUN	15	conj
25	de	ADP	26	case
26	Ciencia	PROPN	24	nmod
27	y	CCONJ	28	cc
28	Tecnología	PROPN	26	conj
29	,	PUNCT	30	punct
30	Carlos	PROPN	24	appos
31	Genatios	PROPN	30	flat
32	,	PUNCT	30	punct
33	y	CCONJ	36	cc
34	con	ADP	36	case
35	el	DET	36	det
36	gobernador	NOUN	15	conj
37	de	ADP	39	case
38	esa	DET	39	det
39	región	NOUN	36	nmod
40	,	PUNCT	41	punct
41	Alfredo	PROPN	36	appos
42	Laya	PROPN	41	flat
43	,	PUNCT	41	punct
44	la	DET	46	det
45	más	ADV	46	advmod
46	castigada	ADJ	6	obj
47	por	ADP	49	case
48	las	DET	49	det
49	lluvias	NOUN	46	obj
50	.	PUNCT	6	punct