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 fuego de Cazorla devoró 836 hectáreas de pino, muy cercanas al núcleo turístico de Arroyo Frío, en el que un 15% de los visitantes proceden de Catalunya, "un mercado creciente y clave" en el desarrollo del ocio de este lugar que tiene 2.000 plazas hoteleras de las 9.000 distribuidas por la reserva, según explicó el presidente de la Federación de Hoteleros de Jaén, Luis Carlos García.
Postion	Tokenization
1	El
2	fuego
3	de
4	Cazorla
5	devoró
6	836
7	hectáreas
8	de
9	pino
10	,
11	muy
12	cercanas
13	al
14	núcleo
15	turístico
16	de
17	Arroyo
18	Frío
19	,
20	en
21	el
22	que
23	un
24	15%
25	de
26	los
27	visitantes
28	proceden
29	de
30	Catalunya
31	,
32	"
33	un
34	mercado
35	creciente
36	y
37	clave
38	"
39	en
40	el
41	desarrollo
42	del
43	ocio
44	de
45	este
46	lugar
47	que
48	tiene
49	2.000
50	plazas
51	hoteleras
52	de
53	las
54	9.000
55	distribuidas
56	por
57	la
58	reserva
59	,
60	según
61	explicó
62	el
63	presidente
64	de
65	la
66	Federación
67	de
68	Hoteleros
69	de
70	Jaén
71	,
72	Luis
73	Carlos
74	García
75	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	fuego	NOUN	5	nsubj
3	de	ADP	4	case
4	Cazorla	PROPN	2	nmod
5	devoró	VERB	0	root
6	836	NUM	7	nummod
7	hectáreas	NOUN	5	obj
8	de	ADP	9	case
9	pino	NOUN	7	nmod
10	,	PUNCT	12	punct
11	muy	ADV	12	advmod
12	cercanas	ADJ	7	amod
13	al	ADP	14	case
14	núcleo	NOUN	12	nmod
15	turístico	ADJ	14	amod
16	de	ADP	17	case
17	Arroyo	PROPN	14	nmod
18	Frío	PROPN	17	flat
19	,	PUNCT	28	punct
20	en	ADP	22	case
21	el	DET	22	det
22	que	PRON	28	obl
23	un	DET	24	det
24	15%	SYM	28	nsubj
25	de	ADP	27	case
26	los	DET	27	det
27	visitantes	NOUN	24	nmod
28	proceden	VERB	14	acl
29	de	ADP	30	case
30	Catalunya	PROPN	28	obj
31	,	PUNCT	34	punct
32	"	PUNCT	34	punct
33	un	DET	34	det
34	mercado	NOUN	30	appos
35	creciente	ADJ	34	amod
36	y	CCONJ	37	cc
37	clave	NOUN	34	conj
38	"	PUNCT	37	punct
39	en	ADP	41	case
40	el	DET	41	det
41	desarrollo	NOUN	37	nmod
42	del	ADP	43	case
43	ocio	NOUN	41	nmod
44	de	ADP	46	case
45	este	DET	46	det
46	lugar	NOUN	43	nmod
47	que	PRON	48	nsubj
48	tiene	VERB	46	acl
49	2.000	NUM	50	nummod
50	plazas	NOUN	48	obj
51	hoteleras	ADJ	50	amod
52	de	ADP	54	case
53	las	DET	54	det
54	9.000	NUM	50	nummod
55	distribuidas	ADJ	54	advmod
56	por	ADP	58	case
57	la	DET	58	det
58	reserva	NOUN	55	obl
59	,	PUNCT	61	punct
60	según	SCONJ	61	mark
61	explicó	VERB	48	advcl
62	el	DET	63	det
63	presidente	NOUN	61	nsubj
64	de	ADP	66	case
65	la	DET	66	det
66	Federación	PROPN	63	nmod
67	de	ADP	68	case
68	Hoteleros	PROPN	66	flat
69	de	ADP	70	case
70	Jaén	PROPN	66	flat
71	,	PUNCT	72	punct
72	Luis	PROPN	63	appos
73	Carlos	PROPN	72	flat
74	García	PROPN	72	flat
75	.	PUNCT	5	punct