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 también crecen muy por encima de la media (un 10,2 por ciento) en Melilla (99,8 %), Andalucía (71 %), Cantabria (68,8 %) y Aragón (65,7 %).
Postion	Tokenization
1	Las
2	inversiones
3	también
4	crecen
5	muy
6	por
7	encima
8	de
9	la
10	media
11	(
12	un
13	10,2
14	por
15	ciento
16	)
17	en
18	Melilla
19	(
20	99,8
21	%
22	)
23	,
24	Andalucía
25	(
26	71
27	%
28	)
29	,
30	Cantabria
31	(
32	68,8
33	%
34	)
35	y
36	Aragón
37	(
38	65,7
39	%
40	)
41	.
Position	Tokenization	UPOS	Head	Deprel
1	Las	DET	2	det
2	inversiones	NOUN	4	nsubj
3	también	ADV	4	advmod
4	crecen	VERB	0	root
5	muy	ADV	4	advmod
6	por	ADP	5	case
7	encima	ADV	6	fixed
8	de	ADP	6	fixed
9	la	DET	10	det
10	media	NOUN	5	nmod
11	(	PUNCT	13	punct
12	un	DET	13	det
13	10,2	NUM	10	appos
14	por	ADP	15	case
15	ciento	NUM	13	compound
16	)	PUNCT	13	punct
17	en	ADP	18	case
18	Melilla	PROPN	4	obl
19	(	PUNCT	20	punct
20	99,8	NUM	18	appos
21	%	SYM	20	nmod
22	)	PUNCT	20	punct
23	,	PUNCT	24	punct
24	Andalucía	PROPN	18	conj
25	(	PUNCT	26	punct
26	71	NUM	24	appos
27	%	SYM	26	nmod
28	)	PUNCT	26	punct
29	,	PUNCT	30	punct
30	Cantabria	PROPN	18	conj
31	(	PUNCT	32	punct
32	68,8	NUM	30	appos
33	%	SYM	32	nmod
34	)	PUNCT	32	punct
35	y	CCONJ	36	cc
36	Aragón	PROPN	18	conj
37	(	PUNCT	38	punct
38	65,7	NUM	36	appos
39	%	SYM	38	nmod
40	)	PUNCT	38	punct
41	.	PUNCT	4	punct