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 inversiones del Estado, la Seguridad Social y los Organismos públicos crecen menos que la media, además de en Cataluña y Galicia, en Canarias (6,3 %).
Postion	Tokenization
1	Las
2	inversiones
3	del
4	Estado
5	,
6	la
7	Seguridad
8	Social
9	y
10	los
11	Organismos
12	públicos
13	crecen
14	menos
15	que
16	la
17	media
18	,
19	además
20	de
21	en
22	Cataluña
23	y
24	Galicia
25	,
26	en
27	Canarias
28	(
29	6,3
30	%
31	)
32	.
Position	Tokenization	UPOS	Head	Deprel
1	Las	DET	2	det
2	inversiones	NOUN	13	nsubj
3	del	ADP	4	case
4	Estado	PROPN	2	nmod
5	,	PUNCT	7	punct
6	la	DET	7	det
7	Seguridad	PROPN	4	flat
8	Social	PROPN	7	flat
9	y	CCONJ	11	cc
10	los	DET	11	det
11	Organismos	PROPN	4	conj
12	públicos	ADJ	11	amod
13	crecen	VERB	0	root
14	menos	ADV	13	advmod
15	que	SCONJ	17	mark
16	la	DET	17	det
17	media	NOUN	14	obl
18	,	PUNCT	19	punct
19	además	ADV	13	advmod
20	de	ADP	22	case
21	en	ADP	22	case
22	Cataluña	PROPN	19	obl
23	y	CCONJ	24	cc
24	Galicia	PROPN	22	conj
25	,	PUNCT	19	punct
26	en	ADP	19	case
27	Canarias	PROPN	19	nmod
28	(	PUNCT	29	punct
29	6,3	NUM	13	obl
30	%	SYM	29	nmod
31	)	PUNCT	29	punct
32	.	PUNCT	13	punct