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:
"Las dificultades que tiene un acto tan masivo, con 90.000 asistentes, no son muy distintas de las de uno para 15.000 personas", afirma el director.
Postion	Tokenization
1	"
2	Las
3	dificultades
4	que
5	tiene
6	un
7	acto
8	tan
9	masivo
10	,
11	con
12	90.000
13	asistentes
14	,
15	no
16	son
17	muy
18	distintas
19	de
20	las
21	de
22	uno
23	para
24	15.000
25	personas
26	"
27	,
28	afirma
29	el
30	director
31	.
Position	Tokenization	UPOS	Head	Deprel
1	"	PUNCT	18	punct
2	Las	DET	3	det
3	dificultades	NOUN	18	nsubj
4	que	PRON	5	obj
5	tiene	VERB	3	acl
6	un	DET	7	det
7	acto	NOUN	5	nsubj
8	tan	ADV	9	advmod
9	masivo	ADJ	7	amod
10	,	PUNCT	13	punct
11	con	ADP	13	case
12	90.000	NUM	13	nummod
13	asistentes	NOUN	7	nmod
14	,	PUNCT	13	punct
15	no	ADV	18	advmod
16	son	AUX	18	cop
17	muy	ADV	18	advmod
18	distintas	ADJ	28	ccomp
19	de	ADP	20	case
20	las	DET	18	det
21	de	ADP	20	case
22	uno	PRON	20	nmod
23	para	ADP	25	case
24	15.000	NUM	25	nummod
25	personas	NOUN	22	nmod
26	"	PUNCT	18	punct
27	,	PUNCT	18	punct
28	afirma	VERB	0	root
29	el	DET	30	det
30	director	NOUN	28	nsubj
31	.	PUNCT	28	punct