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:
En una escena típica del más riguroso invierno y no de un puente del 1 de mayo, unidades de tráfico de los Mossos d'Esquadra acompañadas de máquinas quitanieves sólo permitían circular por la mañana a partir de Vilaller (Alta Ribagorça) a vehículos con cadenas.
Postion	Tokenization
1	En
2	una
3	escena
4	típica
5	del
6	más
7	riguroso
8	invierno
9	y
10	no
11	de
12	un
13	puente
14	del
15	1
16	de
17	mayo
18	,
19	unidades
20	de
21	tráfico
22	de
23	los
24	Mossos
25	d'Esquadra
26	acompañadas
27	de
28	máquinas
29	quitanieves
30	sólo
31	permitían
32	circular
33	por
34	la
35	mañana
36	a
37	partir
38	de
39	Vilaller
40	(
41	Alta
42	Ribagorça
43	)
44	a
45	vehículos
46	con
47	cadenas
48	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	3	case
2	una	DET	3	det
3	escena	NOUN	31	obl
4	típica	ADJ	3	amod
5	del	ADP	8	case
6	más	ADV	7	advmod
7	riguroso	ADJ	8	amod
8	invierno	NOUN	4	nmod
9	y	CCONJ	10	cc
10	no	ADV	8	conj
11	de	ADP	10	case
12	un	DET	13	det
13	puente	NOUN	10	nmod
14	del	ADP	15	case
15	1	NUM	13	nmod
16	de	ADP	17	case
17	mayo	NOUN	15	compound
18	,	PUNCT	3	punct
19	unidades	NOUN	31	nsubj
20	de	ADP	21	case
21	tráfico	NOUN	19	nmod
22	de	ADP	24	case
23	los	DET	24	det
24	Mossos	PROPN	19	nmod
25	d'Esquadra	PROPN	24	flat
26	acompañadas	ADJ	19	amod
27	de	ADP	28	case
28	máquinas	NOUN	26	obj
29	quitanieves	ADJ	28	amod
30	sólo	ADV	31	advmod
31	permitían	VERB	0	root
32	circular	VERB	31	xcomp
33	por	ADP	35	case
34	la	DET	35	det
35	mañana	NOUN	32	obl
36	a	ADP	39	case
37	partir	NOUN	36	fixed
38	de	ADP	36	fixed
39	Vilaller	PROPN	32	obl
40	(	PUNCT	41	punct
41	Alta	PROPN	39	flat
42	Ribagorça	PROPN	41	flat
43	)	PUNCT	41	punct
44	a	ADP	45	case
45	vehículos	NOUN	31	iobj
46	con	ADP	47	case
47	cadenas	NOUN	45	nmod
48	.	PUNCT	31	punct