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:
Laila, de 21 años, es la Segunda más pequeña de los nueve hijos de Ali, enfermo de Parkinson, quien no ha visto con buenos ojos que se dedique a este violento deporte porque no quiere que sufra daños y considera que se trata de un negocio corrupto.
Postion	Tokenization
1	Laila
2	,
3	de
4	21
5	años
6	,
7	es
8	la
9	Segunda
10	más
11	pequeña
12	de
13	los
14	nueve
15	hijos
16	de
17	Ali
18	,
19	enfermo
20	de
21	Parkinson
22	,
23	quien
24	no
25	ha
26	visto
27	con
28	buenos
29	ojos
30	que
31	se
32	dedique
33	a
34	este
35	violento
36	deporte
37	porque
38	no
39	quiere
40	que
41	sufra
42	daños
43	y
44	considera
45	que
46	se
47	trata
48	de
49	un
50	negocio
51	corrupto
52	.
Position	Tokenization	UPOS	Head	Deprel
1	Laila	PROPN	9	nsubj
2	,	PUNCT	5	punct
3	de	ADP	5	case
4	21	NUM	5	nummod
5	años	NOUN	1	nmod
6	,	PUNCT	5	punct
7	es	AUX	9	cop
8	la	DET	9	det
9	Segunda	ADJ	0	root
10	más	ADV	11	advmod
11	pequeña	ADJ	9	amod
12	de	ADP	15	case
13	los	DET	15	det
14	nueve	NUM	13	nummod
15	hijos	NOUN	9	nmod
16	de	ADP	17	case
17	Ali	PROPN	15	nmod
18	,	PUNCT	19	punct
19	enfermo	NOUN	17	appos
20	de	ADP	21	case
21	Parkinson	PROPN	19	nmod
22	,	PUNCT	19	punct
23	quien	PRON	26	nsubj
24	no	ADV	26	advmod
25	ha	AUX	26	aux
26	visto	VERB	17	acl
27	con	ADP	29	case
28	buenos	ADJ	29	amod
29	ojos	NOUN	26	obl
30	que	SCONJ	32	mark
31	se	PRON	32	expl:pv
32	dedique	VERB	26	ccomp
33	a	ADP	36	case
34	este	DET	36	det
35	violento	ADJ	36	amod
36	deporte	NOUN	32	obj
37	porque	SCONJ	39	mark
38	no	ADV	39	advmod
39	quiere	VERB	26	advcl
40	que	SCONJ	41	mark
41	sufra	VERB	39	ccomp
42	daños	NOUN	41	obj
43	y	CCONJ	44	cc
44	considera	VERB	39	conj
45	que	SCONJ	47	mark
46	se	PRON	47	expl:impers
47	trata	VERB	44	ccomp
48	de	ADP	50	case
49	un	DET	50	det
50	negocio	NOUN	47	obj
51	corrupto	ADJ	50	amod
52	.	PUNCT	9	punct