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:
Durante algún tiempo la idea de una diligencia a vapor persistió entre los inventores, y el propio Richard Trevithick, que tanto contribuiría al desarrollo del tren, presentó en 1801 el primer coche de vapor que circuló realmente por las calles de Londres.
Postion	Tokenization
1	Durante
2	algún
3	tiempo
4	la
5	idea
6	de
7	una
8	diligencia
9	a
10	vapor
11	persistió
12	entre
13	los
14	inventores
15	,
16	y
17	el
18	propio
19	Richard
20	Trevithick
21	,
22	que
23	tanto
24	contribuiría
25	al
26	desarrollo
27	del
28	tren
29	,
30	presentó
31	en
32	1801
33	el
34	primer
35	coche
36	de
37	vapor
38	que
39	circuló
40	realmente
41	por
42	las
43	calles
44	de
45	Londres
46	.
Position	Tokenization	UPOS	Head	Deprel
1	Durante	ADP	3	case
2	algún	DET	3	det
3	tiempo	NOUN	11	obl
4	la	DET	5	det
5	idea	NOUN	11	nsubj
6	de	ADP	8	case
7	una	DET	8	det
8	diligencia	NOUN	5	nmod
9	a	ADP	10	case
10	vapor	NOUN	8	nmod
11	persistió	VERB	0	root
12	entre	ADP	14	case
13	los	DET	14	det
14	inventores	NOUN	11	obl
15	,	PUNCT	30	punct
16	y	CCONJ	30	cc
17	el	DET	19	det
18	propio	DET	17	det
19	Richard	PROPN	30	nsubj
20	Trevithick	PROPN	19	flat
21	,	PUNCT	24	punct
22	que	PRON	24	nsubj
23	tanto	ADV	24	advmod
24	contribuiría	VERB	19	acl
25	al	ADP	26	case
26	desarrollo	NOUN	24	obj
27	del	ADP	28	case
28	tren	NOUN	26	nmod
29	,	PUNCT	24	punct
30	presentó	VERB	11	conj
31	en	ADP	32	case
32	1801	NOUN	30	obl
33	el	DET	35	det
34	primer	ADJ	35	amod
35	coche	NOUN	30	obj
36	de	ADP	37	case
37	vapor	NOUN	35	nmod
38	que	PRON	39	nsubj
39	circuló	VERB	35	acl
40	realmente	ADV	39	advmod
41	por	ADP	43	case
42	las	DET	43	det
43	calles	NOUN	39	obl
44	de	ADP	45	case
45	Londres	PROPN	43	nmod
46	.	PUNCT	11	punct