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:
Según la NIAA, la explotación ilegal del arte aborigen, que representa unos ingresos de más de 100 millones de dólares para el Gobierno y que generará otros 25 millones más durante los Juegos, evita que este dinero llegue a las comunidades de donde provienen las obras de arte auténticas.
Postion	Tokenization
1	Según
2	la
3	NIAA
4	,
5	la
6	explotación
7	ilegal
8	del
9	arte
10	aborigen
11	,
12	que
13	representa
14	unos
15	ingresos
16	de
17	más
18	de
19	100
20	millones
21	de
22	dólares
23	para
24	el
25	Gobierno
26	y
27	que
28	generará
29	otros
30	25
31	millones
32	más
33	durante
34	los
35	Juegos
36	,
37	evita
38	que
39	este
40	dinero
41	llegue
42	a
43	las
44	comunidades
45	de
46	donde
47	provienen
48	las
49	obras
50	de
51	arte
52	auténticas
53	.
Position	Tokenization	UPOS	Head	Deprel
1	Según	ADP	3	case
2	la	DET	3	det
3	NIAA	PROPN	37	obl
4	,	PUNCT	3	punct
5	la	DET	6	det
6	explotación	NOUN	37	nsubj
7	ilegal	ADJ	6	amod
8	del	ADP	9	case
9	arte	NOUN	6	nmod
10	aborigen	ADJ	9	amod
11	,	PUNCT	13	punct
12	que	PRON	13	nsubj
13	representa	VERB	6	acl
14	unos	DET	15	det
15	ingresos	NOUN	13	obj
16	de	ADP	20	case
17	más	ADV	20	advmod
18	de	ADP	17	case
19	100	NUM	17	nummod
20	millones	NOUN	15	nmod
21	de	ADP	22	case
22	dólares	NOUN	20	nmod
23	para	ADP	25	case
24	el	DET	25	det
25	Gobierno	PROPN	15	nmod
26	y	CCONJ	28	cc
27	que	PRON	28	nsubj
28	generará	VERB	13	conj
29	otros	PRON	30	nmod
30	25	NUM	31	nummod
31	millones	NOUN	28	obj
32	más	ADV	31	advmod
33	durante	ADP	35	case
34	los	DET	35	det
35	Juegos	PROPN	28	obl
36	,	PUNCT	13	punct
37	evita	VERB	0	root
38	que	SCONJ	41	mark
39	este	DET	40	det
40	dinero	NOUN	41	nsubj
41	llegue	VERB	37	ccomp
42	a	ADP	44	case
43	las	DET	44	det
44	comunidades	NOUN	41	obl
45	de	ADP	46	case
46	donde	PRON	47	obj
47	provienen	VERB	44	acl
48	las	DET	49	det
49	obras	NOUN	47	nsubj
50	de	ADP	51	case
51	arte	NOUN	49	nmod
52	auténticas	ADJ	49	amod
53	.	PUNCT	37	punct