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:
Tras muchas pruebas y retoques, registró varias patentes y obtuvo sucesivos éxitos con sus motores, que vendía a millares, especialmente a las pequeñas industrias para las que una máquina de vapor era demasiado grande.
Postion	Tokenization
1	Tras
2	muchas
3	pruebas
4	y
5	retoques
6	,
7	registró
8	varias
9	patentes
10	y
11	obtuvo
12	sucesivos
13	éxitos
14	con
15	sus
16	motores
17	,
18	que
19	vendía
20	a
21	millares
22	,
23	especialmente
24	a
25	las
26	pequeñas
27	industrias
28	para
29	las
30	que
31	una
32	máquina
33	de
34	vapor
35	era
36	demasiado
37	grande
38	.
Position	Tokenization	UPOS	Head	Deprel
1	Tras	ADP	3	case
2	muchas	DET	3	det
3	pruebas	NOUN	7	obl
4	y	CCONJ	5	cc
5	retoques	NOUN	3	conj
6	,	PUNCT	3	punct
7	registró	VERB	0	root
8	varias	DET	9	det
9	patentes	NOUN	7	obj
10	y	CCONJ	11	cc
11	obtuvo	VERB	7	conj
12	sucesivos	ADJ	13	amod
13	éxitos	NOUN	11	obj
14	con	ADP	16	case
15	sus	DET	16	det
16	motores	NOUN	11	obl
17	,	PUNCT	19	punct
18	que	PRON	19	obj
19	vendía	VERB	16	acl
20	a	ADP	21	case
21	millares	NOUN	19	obl
22	,	PUNCT	23	punct
23	especialmente	ADV	19	obj
24	a	ADP	23	case
25	las	DET	27	det
26	pequeñas	ADJ	27	amod
27	industrias	NOUN	23	nmod
28	para	ADP	30	case
29	las	DET	30	det
30	que	PRON	37	obl
31	una	DET	32	det
32	máquina	NOUN	37	nsubj
33	de	ADP	34	case
34	vapor	NOUN	32	nmod
35	era	AUX	37	cop
36	demasiado	ADV	37	advmod
37	grande	ADJ	27	acl
38	.	PUNCT	7	punct