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:
Do role hrůzného umělého člověka v nejnovější verzi proslulého románu Mary Shelleyové FRANKENSTEIN (1994) obsadil producent Francis Ford Coppola herce Roberta De Nira.
Postion	Tokenization
1	Do
2	role
3	hrůzného
4	umělého
5	člověka
6	v
7	nejnovější
8	verzi
9	proslulého
10	románu
11	Mary
12	Shelleyové
13	FRANKENSTEIN
14	(
15	1994
16	)
17	obsadil
18	producent
19	Francis
20	Ford
21	Coppola
22	herce
23	Roberta
24	De
25	Nira
26	.
Position	Tokenization	UPOS	Head	Deprel
1	Do	ADP	2	case
2	role	NOUN	17	obl
3	hrůzného	ADJ	5	amod
4	umělého	ADJ	5	amod
5	člověka	NOUN	2	nmod
6	v	ADP	8	case
7	nejnovější	ADJ	8	amod
8	verzi	NOUN	5	nmod
9	proslulého	ADJ	10	amod
10	románu	NOUN	8	nmod
11	Mary	PROPN	10	nmod
12	Shelleyové	PROPN	11	flat
13	FRANKENSTEIN	PROPN	10	nmod
14	(	PUNCT	13	punct
15	1994	NUM	13	dep
16	)	PUNCT	13	punct
17	obsadil	VERB	0	root
18	producent	NOUN	17	nsubj
19	Francis	PROPN	18	flat
20	Ford	PROPN	18	flat
21	Coppola	PROPN	18	flat
22	herce	NOUN	17	obj
23	Roberta	PROPN	22	flat
24	De	ADP	22	flat
25	Nira	PROPN	22	flat
26	.	PUNCT	17	punct