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:
Desde siempre, el hombre había soñado con la posibilidad de generar vida artificial, ya fuera ensamblando bielas y engranajes, o manipulando órganos y tejidos en los sótanos de hospitales y laboratorios, como hacía el doctor Frankenstein, para conseguir un autómata capaz de emular algunas de las actividades propias de los seres vivos.
Postion	Tokenization
1	Desde
2	siempre
3	,
4	el
5	hombre
6	había
7	soñado
8	con
9	la
10	posibilidad
11	de
12	generar
13	vida
14	artificial
15	,
16	ya
17	fuera
18	ensamblando
19	bielas
20	y
21	engranajes
22	,
23	o
24	manipulando
25	órganos
26	y
27	tejidos
28	en
29	los
30	sótanos
31	de
32	hospitales
33	y
34	laboratorios
35	,
36	como
37	hacía
38	el
39	doctor
40	Frankenstein
41	,
42	para
43	conseguir
44	un
45	autómata
46	capaz
47	de
48	emular
49	algunas
50	de
51	las
52	actividades
53	propias
54	de
55	los
56	seres
57	vivos
58	.
Position	Tokenization	UPOS	Head	Deprel
1	Desde	ADP	2	case
2	siempre	ADV	7	advmod
3	,	PUNCT	2	punct
4	el	DET	5	det
5	hombre	NOUN	7	nsubj
6	había	AUX	7	aux
7	soñado	VERB	0	root
8	con	ADP	10	case
9	la	DET	10	det
10	posibilidad	NOUN	7	obj
11	de	ADP	12	mark
12	generar	VERB	10	acl
13	vida	NOUN	12	iobj
14	artificial	ADJ	13	amod
15	,	PUNCT	18	punct
16	ya	ADV	18	advmod
17	fuera	AUX	18	aux
18	ensamblando	VERB	10	ccomp
19	bielas	NOUN	18	obj
20	y	CCONJ	21	cc
21	engranajes	NOUN	19	conj
22	,	PUNCT	24	punct
23	o	CCONJ	24	cc
24	manipulando	VERB	18	conj
25	órganos	NOUN	24	obj
26	y	CCONJ	27	cc
27	tejidos	NOUN	25	conj
28	en	ADP	30	case
29	los	DET	30	det
30	sótanos	NOUN	24	obl
31	de	ADP	32	case
32	hospitales	NOUN	30	nmod
33	y	CCONJ	34	cc
34	laboratorios	NOUN	32	conj
35	,	PUNCT	37	punct
36	como	SCONJ	37	mark
37	hacía	VERB	24	advcl
38	el	DET	39	det
39	doctor	NOUN	37	nsubj
40	Frankenstein	PROPN	39	appos
41	,	PUNCT	43	punct
42	para	ADP	43	mark
43	conseguir	VERB	18	advcl
44	un	DET	45	det
45	autómata	NOUN	43	obj
46	capaz	ADJ	45	amod
47	de	ADP	48	mark
48	emular	VERB	46	ccomp
49	algunas	PRON	48	obj
50	de	ADP	52	case
51	las	DET	52	det
52	actividades	NOUN	49	nmod
53	propias	ADJ	52	amod
54	de	ADP	56	case
55	los	DET	56	det
56	seres	NOUN	53	obl
57	vivos	ADJ	56	amod
58	.	PUNCT	7	punct