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:
En Cataluña las inversiones disminuyen un diez por ciento, mientras que en Galicia se mantienen prácticamente en el mismo nivel que en el último ejercicio (registran un incremento del 0,3 por ciento).
Postion	Tokenization
1	En
2	Cataluña
3	las
4	inversiones
5	disminuyen
6	un
7	diez
8	por
9	ciento
10	,
11	mientras
12	que
13	en
14	Galicia
15	se
16	mantienen
17	prácticamente
18	en
19	el
20	mismo
21	nivel
22	que
23	en
24	el
25	último
26	ejercicio
27	(
28	registran
29	un
30	incremento
31	del
32	0,3
33	por
34	ciento
35	)
36	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	2	case
2	Cataluña	PROPN	5	obl
3	las	DET	4	det
4	inversiones	NOUN	5	nsubj
5	disminuyen	VERB	11	parataxis
6	un	DET	7	det
7	diez	NUM	5	obj
8	por	ADP	9	case
9	ciento	NUM	7	compound
10	,	PUNCT	11	punct
11	mientras	CCONJ	0	root
12	que	SCONJ	11	fixed
13	en	ADP	14	case
14	Galicia	PROPN	16	obl
15	se	PRON	16	expl:pv
16	mantienen	VERB	11	parataxis
17	prácticamente	ADV	16	advmod
18	en	ADP	21	case
19	el	DET	21	det
20	mismo	DET	19	det
21	nivel	NOUN	16	obl
22	que	PRON	21	nmod
23	en	ADP	26	case
24	el	DET	26	det
25	último	ADJ	26	amod
26	ejercicio	NOUN	22	nmod
27	(	PUNCT	28	punct
28	registran	VERB	16	parataxis
29	un	DET	30	det
30	incremento	NOUN	28	obj
31	del	ADP	32	case
32	0,3	NUM	30	nummod
33	por	ADP	34	case
34	ciento	NUM	32	compound
35	)	PUNCT	28	punct
36	.	PUNCT	11	punct