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:
Considerado el país de menor renta per cápita del hemisferio, Haiti tiene una densidad de 270 habitantes por kilómetro cuadrado (en España, por ejemplo, la densidad es de 70) y sus 7,5 millones de ciudadanos se apiñan en las zonas más habitables de su suelo, que ocupa la tercera parte de la isla La Española, compartida con la República Dominicana.
Postion	Tokenization
1	Considerado
2	el
3	país
4	de
5	menor
6	renta
7	per
8	cápita
9	del
10	hemisferio
11	,
12	Haiti
13	tiene
14	una
15	densidad
16	de
17	270
18	habitantes
19	por
20	kilómetro
21	cuadrado
22	(
23	en
24	España
25	,
26	por
27	ejemplo
28	,
29	la
30	densidad
31	es
32	de
33	70
34	)
35	y
36	sus
37	7,5
38	millones
39	de
40	ciudadanos
41	se
42	apiñan
43	en
44	las
45	zonas
46	más
47	habitables
48	de
49	su
50	suelo
51	,
52	que
53	ocupa
54	la
55	tercera
56	parte
57	de
58	la
59	isla
60	La
61	Española
62	,
63	compartida
64	con
65	la
66	República
67	Dominicana
68	.
Position	Tokenization	UPOS	Head	Deprel
1	Considerado	VERB	12	acl
2	el	DET	3	det
3	país	NOUN	1	nsubj
4	de	ADP	6	case
5	menor	ADJ	6	amod
6	renta	NOUN	3	nmod
7	per	ADP	8	case
8	cápita	NOUN	6	compound
9	del	ADP	10	case
10	hemisferio	NOUN	3	nmod
11	,	PUNCT	1	punct
12	Haiti	PROPN	13	nsubj
13	tiene	VERB	0	root
14	una	DET	15	det
15	densidad	NOUN	13	obj
16	de	ADP	18	case
17	270	NUM	18	nummod
18	habitantes	NOUN	15	nmod
19	por	ADP	20	case
20	kilómetro	NOUN	18	nmod
21	cuadrado	NOUN	20	compound
22	(	PUNCT	33	punct
23	en	ADP	24	case
24	España	PROPN	33	obl
25	,	PUNCT	26	punct
26	por	ADP	24	advmod
27	ejemplo	NOUN	26	fixed
28	,	PUNCT	26	punct
29	la	DET	30	det
30	densidad	NOUN	33	nsubj
31	es	AUX	33	cop
32	de	ADP	33	case
33	70	NUM	15	parataxis
34	)	PUNCT	33	punct
35	y	CCONJ	42	cc
36	sus	PRON	37	nmod
37	7,5	NUM	38	nummod
38	millones	NOUN	42	nsubj
39	de	ADP	40	case
40	ciudadanos	NOUN	38	nmod
41	se	PRON	42	expl:pv
42	apiñan	VERB	13	conj
43	en	ADP	45	case
44	las	DET	45	det
45	zonas	NOUN	42	obj
46	más	ADV	47	advmod
47	habitables	ADJ	45	amod
48	de	ADP	50	case
49	su	DET	50	det
50	suelo	NOUN	45	nmod
51	,	PUNCT	53	punct
52	que	PRON	53	nsubj
53	ocupa	VERB	50	acl
54	la	DET	56	det
55	tercera	ADJ	56	amod
56	parte	NOUN	53	obj
57	de	ADP	59	case
58	la	DET	59	det
59	isla	NOUN	56	nmod
60	La	DET	61	det
61	Española	PROPN	59	appos
62	,	PUNCT	63	punct
63	compartida	ADJ	59	amod
64	con	ADP	66	case
65	la	DET	66	det
66	República	PROPN	63	obl
67	Dominicana	PROPN	66	flat
68	.	PUNCT	13	punct