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:
El paro descendió en 16 comunidades autónomas, encabezadas por Andalucía (8.653), Madrid (7.201) y Baleares (5.729), pero se elevó en 1.298 personas en Canarias.
Postion	Tokenization
1	El
2	paro
3	descendió
4	en
5	16
6	comunidades
7	autónomas
8	,
9	encabezadas
10	por
11	Andalucía
12	(
13	8.653
14	)
15	,
16	Madrid
17	(
18	7.201
19	)
20	y
21	Baleares
22	(
23	5.729
24	)
25	,
26	pero
27	se
28	elevó
29	en
30	1.298
31	personas
32	en
33	Canarias
34	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	paro	NOUN	3	nsubj
3	descendió	VERB	0	root
4	en	ADP	6	case
5	16	NUM	6	nummod
6	comunidades	NOUN	3	obl
7	autónomas	ADJ	6	amod
8	,	PUNCT	9	punct
9	encabezadas	ADJ	6	amod
10	por	ADP	11	case
11	Andalucía	PROPN	9	obj
12	(	PUNCT	13	punct
13	8.653	NUM	11	appos
14	)	PUNCT	13	punct
15	,	PUNCT	16	punct
16	Madrid	PROPN	11	conj
17	(	PUNCT	18	punct
18	7.201	NUM	16	appos
19	)	PUNCT	18	punct
20	y	CCONJ	21	cc
21	Baleares	PROPN	11	conj
22	(	PUNCT	23	punct
23	5.729	NUM	21	appos
24	)	PUNCT	23	punct
25	,	PUNCT	28	punct
26	pero	CCONJ	28	cc
27	se	PRON	28	expl:pv
28	elevó	VERB	3	conj
29	en	ADP	31	case
30	1.298	NUM	31	nummod
31	personas	NOUN	28	obj
32	en	ADP	33	case
33	Canarias	PROPN	28	obl
34	.	PUNCT	3	punct