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:
Na otázku, které z veřejně činných osob důvěřují nejvíce, uváděli dotázaní nejčastěji Václava Havla (16 procent) a Václava Klause (11 procent).
Postion	Tokenization
1	Na
2	otázku
3	,
4	které
5	z
6	veřejně
7	činných
8	osob
9	důvěřují
10	nejvíce
11	,
12	uváděli
13	dotázaní
14	nejčastěji
15	Václava
16	Havla
17	(
18	16
19	procent
20	)
21	a
22	Václava
23	Klause
24	(
25	11
26	procent
27	)
28	.
Position	Tokenization	UPOS	Head	Deprel
1	Na	ADP	2	case
2	otázku	NOUN	12	obl
3	,	PUNCT	9	punct
4	které	DET	9	obl:arg
5	z	ADP	8	case
6	veřejně	ADV	7	advmod
7	činných	ADJ	8	amod
8	osob	NOUN	4	nmod
9	důvěřují	VERB	2	acl:relcl
10	nejvíce	ADV	9	advmod
11	,	PUNCT	9	punct
12	uváděli	VERB	0	root
13	dotázaní	ADJ	12	nsubj
14	nejčastěji	ADV	12	advmod
15	Václava	PROPN	12	obj
16	Havla	PROPN	15	flat
17	(	PUNCT	15	punct
18	16	NUM	19	nummod:gov
19	procent	NOUN	15	dep
20	)	PUNCT	15	punct
21	a	CCONJ	22	cc
22	Václava	PROPN	15	conj
23	Klause	PROPN	22	flat
24	(	PUNCT	22	punct
25	11	NUM	26	nummod:gov
26	procent	NOUN	22	dep
27	)	PUNCT	22	punct
28	.	PUNCT	12	punct