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 sindicatos y las patronales calificaron de demasiado optimistas las previsiones, que incluyen una inflación del 2% y 50.000 nuevos empleos, presentadas por Francesc Homs, conseller de Economia.
Postion	Tokenization
1	Los
2	sindicatos
3	y
4	las
5	patronales
6	calificaron
7	de
8	demasiado
9	optimistas
10	las
11	previsiones
12	,
13	que
14	incluyen
15	una
16	inflación
17	del
18	2%
19	y
20	50.000
21	nuevos
22	empleos
23	,
24	presentadas
25	por
26	Francesc
27	Homs
28	,
29	conseller
30	de
31	Economia
32	.
Position	Tokenization	UPOS	Head	Deprel
1	Los	DET	2	det
2	sindicatos	NOUN	6	nsubj
3	y	CCONJ	5	cc
4	las	DET	5	det
5	patronales	NOUN	2	conj
6	calificaron	VERB	0	root
7	de	ADP	9	case
8	demasiado	ADV	9	advmod
9	optimistas	ADJ	6	obj
10	las	DET	11	det
11	previsiones	NOUN	6	obj
12	,	PUNCT	14	punct
13	que	PRON	14	nsubj
14	incluyen	VERB	11	acl
15	una	DET	16	det
16	inflación	NOUN	14	obj
17	del	ADP	18	case
18	2%	SYM	16	nmod
19	y	CCONJ	22	cc
20	50.000	NUM	22	nummod
21	nuevos	ADJ	22	amod
22	empleos	NOUN	16	conj
23	,	PUNCT	24	punct
24	presentadas	ADJ	11	amod
25	por	ADP	26	case
26	Francesc	PROPN	24	obj
27	Homs	PROPN	26	flat
28	,	PUNCT	29	punct
29	conseller	NOUN	26	appos
30	de	ADP	31	case
31	Economia	PROPN	29	nmod
32	.	PUNCT	6	punct